Publications
Books/Book Chapters:
[B4] Trevor Bonjour, Marina Haliem, Vaneet Aggarwal, Mayank Kejriwal, and Bharat Bhargava. "Multi-agent Game Domain: Monopoly," In A Unifying Framework for Formal Theories of Novelty: Discussions, Guidelines, and Examples for Artificial Intelligence, pp. 97-105. Cham: Springer Nature Switzerland, 2023.
[B3] Vaneet Aggarwal and Mridul Agarwal, "Control of Uncertain Systems," Springer Handbook of Automation (2nd ed.), Jun 2023.
[B2] Vaneet Aggarwal and Tian Lan, "Modeling and Optimization of Latency in Erasure-coded Storage Systems," Now Foundations and Trends in Communication and Information Theory, Vol. 18, No. 3, pp 380-525, Jul 2021.
[B1] Vaneet Aggarwal, Xiaodong Wang, and Zhe Wang, "Joint Energy-Bandwidth Allocation for Multiple Broadcast Channels with Energy Harvesting," Chapter in "Cognitive Radio Networks: Performance, Applications and Technology" published by Nova Science Publishers, 1st quarter, 2018.
Vision/Magazine/Review Articles:
[V7] Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, and Vaneet Aggarwal, "Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions," preprint, Feb 2024.
[V6] Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Weifeng Su, and Mung Chiang, "Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks," IEEE Communications Magazine, vol. 61, no. 12, pp. 54-60, December 2023.
[V5] Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, and Mingwei Xu, "Machine Learning for Robust Network Design: A New Perspective," IEEE Communications Magazine, vol. 61, no. 10, pp. 86-92, October 2023.
[V4] Dixita Limbachiya, Manish K. Gupta, and Vaneet Aggarwal, "10 Years of Natural Data Storage," IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 8, no. 4, pp. 263-275, Dec. 2022, doi: 10.1109/TMBMC.2022.3211446.
[V3] Vaneet Aggarwal, "Machine Learning for Communications," Entropy, 23(7), 831, Jun 2021.
[V2] Seyyedali Hosseinalipour, Christopher G. Brinton, Vaneet Aggarwal, Huaiyu Dai, and Mung Chiang, "From Federated Learning to Fog Learning: Distributed Machine Learning over Heterogeneous Networks," IEEE Communications Magazine, vol. 58, no. 12, pp. 41-47, December 2020, doi: 10.1109/MCOM.001.2000410.
[V1] Saurabh Bagchi, Vaneet Aggarwal, Somali Chaterji, Fred Douglis, Aly El Gamal, Jiawei Han, Brian J. Henz, Hank Hoffmann, Suman Jana, Milind Kulkarni, Felix Xiaozhu Lin, Karen Marais, Prateek Mittal, Shaoshuai Mou, Xiaokang Qiu, and Gesualdo Scutari, "Vision Paper: Grand Challenges in Resilience: Autonomous System Resilience through Design and Runtime Measures," IEEE Open Journal of the Computer Society, vol. 1, pp. 155-172, 2020, doi: 10.1109/OJCS.2020.3006807.
Preprints since May 2023:
[PP13] Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher G. Brinton, "Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis," Apr 2024
[PP12] Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal, "Variance-Reduced Policy Gradient Approaches for Infinite Horizon Average Reward Markov Decision Processes," Apr 2024
[PP11] Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Amrit Singh Bedi, and Dinesh Manocha, "Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic," Mar 2024
[PP10] Swetha Ganesh, Jiayu Chen, Gugan Thoppe, and Vaneet Aggarwal, "Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries," Mar 2024
[PP9] Aditya Malusare and Vaneet Aggarwal, "Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model," Feb 2024
[PP8] Mohammad Pedramfar and Vaneet Aggarwal, "A Generalized Approach to Online Convex Optimization," Feb 2024
[PP7] Qinbo Bai, Washim Uddin Mondal, and Vaneet Aggarwal, "Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm," Feb 2024
[PP6] Aditya Malusare, Harish Kothandaraman, Dipesh Tamboli, Nadia A. Lanman, and Vaneet Aggarwal, "Understanding the Natural Language of DNA using Encoder-Decoder Foundation Models with Byte-level Precision," Nov 2023
[PP5] Bhargav Ganguly and Vaneet Aggarwal, "Quantum Acceleration of Infinite Horizon Average-Reward Reinforcement Learning," Oct 2023
[PP4] Debanjan Konar, Dheeraj Peddireddy, Vaneet Aggarwal, Bijaya K. Panigrahi, "Tensor Ring Optimized Quantum-Enhanced Tensor Neural Networks," Oct 2023.
[PP3] Hanhan Zhou, Tian Lan, and Vaneet Aggarwal, "Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning," Aug 2023
[PP2] Mudit Gaur, Amrit Singh Bedi, Di Wang, and Vaneet Aggarwal, "On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization," Jun 2023
[PP1] Jiayu Chen, Tian Lan, and Vaneet Aggarwal, "Hierarchical Deep Counterfactual Regret Minimization," May 2023
Core A*/A Conference Publications with At-Least 7 pages:
[AC49] Washim Uddin Mondal and Vaneet Aggarwal, "Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes," in Proc. AISTATS, May 2024.
[AC48] Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, and Vaneet Aggarwal, "Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization," in Proc. ICLR, May 2024.
[AC47] Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang, "Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model," in Proc. ICLR, May 2024.
[AC46] Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, and Vaneet Aggarwal, "Combinatorial Stochastic-Greedy Bandit," in Proc. AAAI, Feb 2024.
[AC45] Qinbo Bai, Washim Uddin Mondal, and Vaneet Aggarwal, "Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes," in Proc. AAAI, Feb 2024.
[AC44] Mohammad Pedramfar, Christopher John Quinn, and Vaneet Aggarwal, "A Unified Approach for Maximizing Continuous DR-submodular Functions," in Proc. Neurips, Dec 2023.
[AC43] Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, and Vaneet Aggarwal, "Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning," in Proc. Neurips, Dec 2023.
[AC42] Guangchen Lan, Han Wang, James Anderson, Christopher Brinton, and Vaneet Aggarwal, "Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates," in Proc. Neurips, Dec 2023.
[AC41] Jiayu Chen, Vaneet Aggarwal, and Tian Lan, "ODPP: A Unified Algorithm Framework for Unsupervised Option Discovery based on Determinantal Point Process," in Proc. Neurips, Dec 2023.
[AC40] Guanghui Zhang, Ke Liu, Mengbai Xiao, Bingshu Wang, and Vaneet Aggarwal, "An Intelligent Learning Approach to Achieve Near-Second Low-Latency Live Video Streaming under Highly Fluctuating Networks," in Proc. ACM Multimedia, Oct-Nov 2023.
[AC39] Debabrata Pal, Deeptej More, Sai Bhargav Rongali, Dipesh Tamboli, Vaneet Aggarwal, and Biplab Banerjee, "Domain Adaptive Few-Shot Open-Set Learning," in Proc. ICCV, Oct 2023.
[AC38] Jiayu Chen, Dipesh Tamboli, Tian Lan, and Vaneet Aggarwal, "Multi-task Hierarchical Adversarial Inverse Reinforcement Learning," in Proc. ICML, Jul 2023.
[AC37] Guanyu Nie, Yididiya Y Nadew, Yanhui Zhu, Vaneet Aggarwal, and Christopher John Quinn, "A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback," in Proc. ICML, Jul 2023.
[AC36] Mudit Gaur, Vaneet Aggarwal, and Mridul Agarwal, "On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization," in Proc. ICML, Jul 2023.
[AC35] Fares Fourati, Vaneet Aggarwal, Christopher Quinn, and Mohamed-Slim Alouini, "Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback," in Proc. AISTATS, Apr 2023.
[AC34] Jiayu Chen, Tian Lan, Vaneet Aggarwal, "Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May 2023.
[AC33] Qinbo Bai, Amrit Singh Bedi, and Vaneet Aggarwal, "Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm," in Proc. AAAI, Feb 2023.
[AC32] Jiayu Chen, Jingdi Chen, Tian Lan, and Vaneet Aggarwal, "Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs," in Proc. Neurips, Dec 2022.
[AC31] Hanhan Zhou, Tian Lan, and Vaneet Aggarwal, "PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning," in Proc. Neurips, Dec 2022.
[AC30] Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, and Christopher John Quinn, "An Explore-then-Commit Algorithm for Submodular Maximization Under Full-bandit Feedback," in Proc. UAI, Aug 2022.
[AC29] Washim Uddin Mondal, Vaneet Aggarwal, and Satish V. Ukkusuri, "Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction?," in Proc. UAI, Aug 2022.
[AC28] Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal, "Regret Guarantees for Model-Based Reinforcement Learning with Long-Term Average Constraints," in Proc. UAI, Aug 2022.
[AC27] Trevor Bonjour, Vaneet Aggarwal, and Bharat Bhargava, "Information-Theoretic Approach to Detect Collusion in Multi-Agent Games," in Proc. UAI, Aug 2022.
[AC26] Anis Elgabli, Chaouki Ben Issaid, Amrit Singh Bedi, Ketan Rajawat , Mehdi Bennis, and Vaneet Aggarwal, "FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning," in Proc. ICML, Jul 2022.
[AC25] Mridul Agarwal, Vaneet Aggarwal, and Tian Lan, "Multi-Objective Reinforcement Learning with Non-Linear Scalarization," in Proc. AAMAS, May 2022 (26% acceptance rate, 166/629).
[AC24] Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, and Vaneet Aggarwal, "Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach," in Proc. AAAI, Feb 2022 (15% acceptance rate, 1349/9251).
[AC23] Chenyi Liu, Nan Geng, Vaneet Aggarwal, Tian Lan, Yuan Yang and Mingwei Xu, "CMIX: Deep Multi-agent Reinforcement Learning with Peak and Average Constraints" in Proc. ECML, Sep 2021 (21% acceptance rate, 147/685).
[AC22] Jiayu Chen, Abhishek K. Umrawal, Tian Lan, and Vaneet Aggarwal, "DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery," in Proc. ICAPS, Aug 2021.
[AC21] Mridul Agarwal, Bhargav Ganguly, and Vaneet Aggarwal, "Communication Efficient Parallel Reinforcement Learning," in Proc. UAI, Jul 2021 (26.5% acceptance rate, 206/777).
[AC20] Souvik Das, Anirudh Shankar, and Vaneet Aggarwal, "Training Spiking Neural Networks with a Multi-Agent Evolutionary Robotics Framework," in Proc. GECCO, Jul 2021.
[AC19] Glebys Gonzalez, Mridul Agarwal, Mythra Varun Balakuntala Srinivasa Murthy, Md Masudur Rahman, Upinder Kaur, Juan Wachs, Richard Voyles, Vaneet Aggarwal, and Yexiang Xue, "DESERTS:Delay-Tolerant Semi-Autonomous Robot Teleoperation for Surgery," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May-Jun 2021.
[AC18] Ather Gattami, Qinbo Bai, and Vaneet Agarwal, "Reinforcement Learning for Constrained Markov Decision Processes," in Proc. AISTATS, Apr 2021 (29.8% acceptance rate, 455/1527)
[AC17] Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, and Abhishek Umrawal, "Stochastic Combinatorial Bandits with Linear Space and Non-Linear Feedback," in Proc. ALT, Mar 2021 (PMLR 132:306-339, 2021.) (29.3% acceptance rate, 46/157).
[AC16] Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, and Abhishek Umrawal, "DART: aDaptive Accept RejecT for non-linear top-K subset identification," in Proc. AAAI, Feb 2021 (21% acceptance rate, 1692/7911).
[AC15] Nan Geng, Tian Lan, Vaneet Aggarwal, Yuan Yang, and Mingwei Xu, "A Multi-agent Reinforcement Learning Perspective on Distributed Traffic Engineering," in Proc. IEEE International Conference on Network Protocols (ICNP), Oct 2020 (16.8% acceptance rate, 31/184).
[AC14] Ajay Kumar Badita, Parimal Parag, and Vaneet Aggarwal, “Sequential addition of coded tasks for straggler mitigation,” in Proc. IEEE Infocom, Jul 2020 (19.8% acceptance rate, 268/1354).
[AC13] Wenqi Wang, Yifan Sun, Brian Eriksson, Wenlin Wang, and Vaneet Aggarwal, "Wide Compression: Tensor Ring Nets," in Proc. CVPR, Jun 2018 (29% acceptance rate).
[AC12] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Efficient Low Rank Tensor Ring Completion," in Proc. ICCV, Oct 2017 (28.9% acceptance rate) [Code available on github].
[AC11] Vaneet Aggarwal, Jingxian Fan, and Tian Lan, "Taming Tail Latency for Erasure-coded, Distributed Storage Systems," in Proc. IEEE Infocom, May 2017 (20.9% acceptance rate) (Best-in-Session-Presentation Award in Cloud Storage).
[AC10] Rajarajan Sivaraj, Ioannis Broustis, N.K. Shankaranarayanan, Vaneet Aggarwal, Rittwik Jana, and Prashant Mohapatra, "A QoS-enabled Holistic Optimization Framework for LTE-Advanced Heterogeneous Networks," in Proc. Infocom, Apr 2016 (18.2% acceptance rate).
[AC9] Fernando Stefanello, Vaneet Aggarwal, Luciana S. Buriol, Jose F. Goncalves, and Mauricio G. C. Resende, "A Biased Random-key Genetic Algorithm for Placement of Virtual Machines across Geo-Separated Data Centers," in Proc. Genetic and Evolutionary Computation Conference (GECCO), Jul. 2015.
[AC8] Yu Xiang, Vaneet Aggarwal, Yih-Farn Robin Chen, and Tian Lan, "Taming latency in data center networking with erasure coded files," in Proc. IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 2015 (25.7% acceptance rate).
[AC7] Rajarajan Sivaraj, Ioannis Broustis, N.K. Shankaranarayanan, Vaneet Aggarwal, and Prashant Mohapatra, "Mitigating Macro-Cell Outage in LTE-Advanced Deployments," in Proc. IEEE Infocom, Apr. 2015 (19.3% acceptance rate).
[AC6] Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Joint Latency and Cost Optimization for Erasure-coded Data Center Storage," in Proc. IFIP Performance, Oct. 2014 (27.2% acceptance rate).
[AC5] Athula Balachandran, Jeff Pang, Vaneet Aggarwal, Emir Halepovic, Srinivasan Seshan, Shobha Venkataraman, and He Yan, "Modeling Web Quality-of-Experience on Cellular Networks," in Proc. ACM Mobicom, Sep. 2014 (16.4% acceptance rate).
[AC4] Vaneet Aggarwal, Chao Tian, Vinay Vaishampayan, and Yih-Farn Robin Chen "Distributed Data Storage Systems with Opportunistic Repair," in Proc. IEEE Infocomm, Apr. 2014 (19.3% acceptance rate).
[AC3] Robert Margolies, Ashwin Sridharan, Vaneet Aggarwal, Ritwik Jana, N.K. Shankaranarayanan, Vinay Vaishampayan, and Gil Zussman, "Exploiting Mobility in Proportional Fair Cellular Scheduling: Measurements and Algorithms," in Proc. IEEE Infocomm, Apr. 2014 (19.3% acceptance rate).
[AC2] Pedro Santacruz, Vaneet Aggarwal, and Ashutosh Sabharwal, "Beyond Interference Avoidance: Distributed Sub-network Scheduling in Wireless Networks with Local Views," in Proc. IEEE Infocomm, 2013 (17.4% acceptance rate).
[AC1] Vaneet Aggarwal, A. Robert Calderbank, Vijay Gopalakrishnan, Rittwik Jana, K. K. Ramakrishnan, and Fang Yu, "The Effectiveness of Intelligent Scheduling for Multicast Video-on-Demand," in Proc. ACM Multimedia Conference, Oct. 2009 (16.4% acceptance rate).
Journal Publications:
Papers in Peer-Review (with at least 1 revision round):
[J167] Ammar Haydari, Vaneet Aggarwal, Chen-Nee Chuah, and Michael Zhang, "Constrained Reinforcement Learning for Fair and Environmentally Efficient Traffic Signal Controllers," Submitted to ACM Transactions on Autonomous Transportation Systems, Aug 2023 (Revised Feb 2024)
[J166] Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, and Hongbo Dong, "Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning," Submitted to IEEE Transactions on Networking and Service Management, Jun 2023 (Revised Feb 2024).
Accepted/Published:
[J165] Moonmoon Mohanty, Gaurav Gautam, Vaneet Aggarwal, and Parimal Parag, "Analysis of fork-join scheduling on heterogeneous parallel servers," Accepted with minor revision to IEEE/ACM Transactions on Networking, Mar 2024
[J164] Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri, "Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)," Accepted to Journal of Machine Learning Research, Mar 2024
[J163] Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, and Vaneet Aggarwal, "Reinforced Sequential Decision-Making for Sepsis Treatment: The POSNEGDM Framework with Mortality Classifier and Transformer," Accepted to IEEE Journal of Biomedical and Health Informatics, Mar 2024.
[J162] Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, and Vaneet Aggarwal, "Near-perfect Coverage Manifold Estimation in Cellular Networks via conditional GAN," Accepted to IEEE Networking Letters, Feb 2024
[J161] Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, Brian M. Sadler, and Alec Koppel, "Regret and Belief Complexity Trade-off in Gaussian Process Bandits via Information Thresholding," Accepted to IEEE Transactions on Artificial Intelligence, Oct 2023.
[J160] Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu, and Qing Li, "FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design," Accepted to IEEE/ACM Transactions on Networking, Aug 2023.
[J159] Jiayu Chen, Tian Lan, Vaneet Aggarwal, "Hierarchical Adversarial Inverse Reinforcement Learning," Accepted to IEEE Transactions on Neural Networks and Learning Systems, Aug 2023
[J158] Ciyuan Zhang, Su Wang, Vaneet Aggarwal, and Borja Peleato, “Coded Caching with Heterogeneous User Profiles”, IEEE Transactions on Information Theory, vol. 70, no. 3, pp. 1836-1847, March 2024, doi: 10.1109/TIT.2022.3186210.
[J157] Bhargav Ganguly and Vaneet Aggarwal, "Online Federated Learning via Non-Stationary Detection and Adaptation amidst Concept Drift," IEEE/ACM Transactions on Networking, vol. 32, no. 1, pp. 643-653, Feb. 2024, doi: 10.1109/TNET.2023.3294366.
[J156] Seyyedali Hosseinalipour, Su Wang, Nicolo Michelusi, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, and Mung Chiang, "Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks," IEEE/ACM Transactions on Networking, vol. 32, no. 1, pp. 222-237, Feb. 2024, doi: 10.1109/TNET.2023.3286987.
[J155] Chang-Lin Chen, Bharat Bhargava, Vaneet Aggarwal, Basavaraj Tonshal, and Amrit Gopal, "A Hybrid Deep Reinforcement Learning Approach for Jointly Optimizing Offloading and Resource Management in Vehicular Networks," IEEE Transactions on Vehicular Technology, vol. 73, no. 2, pp. 2456-2467, Feb. 2024, doi: 10.1109/TVT.2023.3312340.
[J154] Ruibo Wang, Washim Uddin Mondal, Mustafa A. Kishk, Vaneet Aggarwal, and Mohamed-Slim Alouini, "Terrain-based Coverage Manifold Estimation: Machine Learning, Stochastic Geometry, or Simulation?," IEEE Open Journal of the Communications Society, IEEE Open Journal of the Communications Society, vol. 5, pp. 633-648, 2024
[J153] Vaneet Aggarwal and Rakhi Pratihar, "Insdel codes from subspace and rank-metric codes," Discrete Mathematics, Volume 347, Issue 1, 113675, Jan 2024.
[J152] Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, and Mung Chiang, "Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point," IEEE/ACM Transactions on Networking, vol. 31, no. 6, pp. 2682-2697, Dec. 2023, doi: 10.1109/TNET.2023.3262482.
[J151] Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, and Vaneet Aggarwal, "Achieving Zero Constraint Violation for Concave Utility Constrained Reinforcement Learning via Primal-Dual Approach," Journal of Artificial Intelligence Research, vol. 78, pp. 977-1018, Dec 2023.
[J150] Zequn Li, Mustafa Lokhandwala, Abubakr O. Al-Abbasi, Vaneet Aggarwal, and Hua Cai, "Integrating reinforcement-learning-based vehicle dispatch algorithm into agent-based modeling of autonomous taxis," Transportation, Nov 2023.
[J149] Md Saquib Saharwardi, Hari Prasad Sadari, Vaneet Aggarwal, Karumuri Ashok, and Ibrahim Hoteit, "Long-term variability in the Arabian Peninsula droughts driven by the Atlantic Multidecadal Oscillation," Earth's future, vol. 11, issue 11, Nov 2023.
[J148] Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Learning Circular Hidden Quantum Markov Models: A Tensor Network Approach," IEEE Transactions on Quantum Engineering, vol. 4, pp. 1-11, 2023, Art no. 3101911, Nov 2023, doi: 10.1109/TQE.2023.3319254.
[J147] Dheeraj Peddireddy, Utkarsh Priyam, and Vaneet Aggarwal, "Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization," Physical Review A, Vol. 108, Iss. 4, Oct 2023
[J146] Xingyu Fu, Dheeraj Peddireddy, Fengfeng Zhou, Yuting Xi, Vaneet Aggarwal, Xingyu Li, and Martin Byung-Guk Jun. "Boundary representation compatible feature recognition for manufacturing CAD models," Manufacturing Letters 35, pp. 895-903, Oct 2023.
[J145] Hanhan Zhou, Tian Lan, and Vaneet Aggarwal, "Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 5, pp. 1351-1361, Oct. 2023.
[J144] Jiayu Chen, Jingdi Chen, Tian Lan, and Vaneet Aggarwal, "Learning Multiagent Options for Tabular Reinforcement Learning using Factor Graphs," IEEE Transactions on Artificial Intelligence, vol. 4, no. 5, pp. 1141-1153, Oct. 2023.
[J143] Washim Uddin Mondal and Vaneet Aggarwal, "Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward," Transactions of Machine Learning Research, Aug 2023.
[J142] Abhishek Kumar Umrawal, Christopher J. Quinn, and Vaneet Aggarwal, "A Community-Aware Framework for Social Influence Maximization," IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), vol. 7, no. 4, pp. 1253-1262, Aug. 2023.
[J141] Guanghui Zhang, Jie Zhang, Yan Liu, Haibo Hu, Jack Y. B. Lee, and Vaneet Aggarwal, "Adaptive Video Streaming with Automatic Quality-of-Experience Optimization," IEEE Transactions on Mobile Computing, vol. 22, no. 8, pp. 4456-4470, Aug. 2023.
[J140] Divija Swetha Gadiraju, V. Lalitha, and Vaneet Aggarwal, "An Optimization Framework based on Deep Reinforcement Learning Approaches for Prism Blockchain," IEEE Transactions on Services Computing, vol. 16, no. 4, pp. 2451-2461, 1 July-Aug. 2023
[J139] Fanglin Bao, Xueji Wang, Shree Hari Sureshbabu, Gautam Sreekumar, Li-Ping Yang, Vaneet Aggarwal, Vishnu Boddeti, and Zubin Jacob, "Heat Assisted Detection and Ranging," Nature, 619, pages743–748, Jul 2023 (Featured on the Nature Cover Page).
[J138] Dheeraj Peddireddy, Vipul Bansal, and Vaneet Aggarwal, "Classical simulation of variational quantum classifiers using tensor rings," Applied Soft Computing, Volume 141, 110308, July 2023.
[J137] Xingyu Fu, Fengfeng Zhou, Dheeraj Peddireddy, Zhengyang Kang, Martin Byung-Guk Jun, and Vaneet Aggarwal, "An FEA surrogate model with Boundary Oriented Graph Embedding approach," Journal of Computational Design and Engineering, Volume 10, Issue 3, Pages 1026–1046, June 2023.
[J136] Washim Uddin Mondal, Vaneet Aggarwal, and Satish V. Ukkusuri, "Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State," Transactions on Machine Learning Research, May 2023
[J135] Nan Geng, Qinbo Bai, Chenyi Liu, Tian Lan, Vaneet Aggarwal, Yuan Yang, and Mingwei Xu, "A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints," IEEE Transactions on Vehicular Technology (TVT), vol. 72, no. 5, pp. 6753-6764, May 2023.
[J134] Qinbo Bai, Vaneet Aggarwal, Ather Gattami, "Provably Efficient Model-Free Algorithm for MDPs with Peak Constraints," Journal of Machine Learning Research, 24(60), pp.1−25, Apr 2023.
[J133] Mridul Agarwal and Vaneet Aggarwal, "Reinforcement Learning for Joint Optimization of Multiple Rewards," Journal of Machine Learning Research, 24(49), pp.1−41, Apr 2023.
[J132] Guanghui Zhang, Jie Zhang, Ke Liu, Jing Guo, Jack Y. B. Lee, Haibo Hu, and Vaneet Aggarwal, "DUASVS: A Mobile Data Saving Strategy in Short-form Video Streaming," IEEE Transactions on Services Computing, vol. 16, no. 2, pp. 1066-1078, March-April 2023, doi: 10.1109/TSC.2022.3150012.
[J131] Chang-Lin Chen, Christopher G. Brinton, and Vaneet Aggarwal, "Latency Minimization for Mobile Edge Computing Networks," IEEE Transactions on Mobile Computing, vol. 22, no. 4, pp. 2233-2247, 1 April 2023, doi: 10.1109/TMC.2021.3117511.
[J130] Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangia, and Vaneet Aggarwal, "A Shallow Hybrid Classical-Quantum Spiking Feedforward Neural Network for Noise-Robust Image Classification," Applied Soft Computing, vol. 136, paper 110099, Mar 2023
[J129] Adel Alahmadi, Selda Çalkavur, Patrick Solé, Abdul Nadim Khan, Mohd Arif Raza, and Vaneet Aggarwal, "A new code based signature scheme for Blockchain technology," Mathematics, Feb 2023.
[J128] Glebys Gonzalez, Mythra Balakuntala, Mridul Agarwal, Tomas Low, Bruce Knoth, Andrew W Kirkpatrick, Jessica McKee, Gregory Hager, Vaneet Aggarwal, Yexiang Xue, Richard Voyles, and Juan Wachs, "ASAP: A Semi-Autonomous Precise System for Telesurgery during Communication Delays," IEEE Transactions on Medical Robotics and Bionics, vol. 5, no. 1, pp. 66-78, Feb. 2023, doi: 10.1109/TMRB.2023.3239674
[J127] Guanghui Zhang, Ke Liu, Haibo Hu, Vaneet Aggarwal, and Jack Y. B. Lee, "Post-Streaming Wastage Analysis – A Data Wastage Aware Framework in Mobile Video Streaming," IEEE Transactions on Mobile Computing, vol. 22, no. 1, pp. 389-401, Jan. 2023, doi: 10.1109/TMC.2021.3069764.
[J126] Mridul Agarwal, Qinbo Bai, and Vaneet Aggarwal, "Concave Utility Reinforcement Learning with Zero-Constraint Violations," Transactions on Machine Learning Research, Dec 2022.
[J125] Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Quantum Causal Inference in the Presence of Hidden Common Causes: an Entropic Approach," Physical Review A, 106, 062425, Dec 2022.
[J124] Xinwu Qian, Shuocheng Guo, and Vaneet Aggarwal, "DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning," Transportation Research Part C, vol. 145, 103923, Dec 2022
[J123] Washim Uddin Mondal, Praful D. Mankar, Goutam Das, Vaneet Aggarwal, and Satish V. Ukkusuri, "Deep Learning based Coverage and Rate Manifold Estimation in Cellular Networks," IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 4, pp. 1706-1715, Dec. 2022, doi: 10.1109/TCCN.2022.3201508.
[J122] Marina Haliem, Trevor Bonjour, Aala Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal, Bharat Bhargava, and Mayank Kejriwal, "Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 6, pp. 1335-1344, Dec. 2022, doi: 10.1109/TETCI.2022.3166555.
[J121] Washim Uddin Mondal, Vaneet Aggarwal, and Satish V. Ukkusuri, "On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning," Transactions on Machine Learning Research, Sep 2022.
[J120] Xingyu Fu, Dheeraj Peddireddy, Vaneet Aggarwal, and Martin Byung-Guk Jun, "Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD," IEEE Transactions on Industrial Informatics, vol. 18, no. 9, pp. 5882-5892, Sept. 2022, doi: 10.1109/TII.2021.3136167.
[J119] Qinbo Bai, Mridul Agarwal, and Vaneet Aggarwal, "Joint Optimization of Concave Scalarized Multi-ObjectiveReinforcement Learning with Policy Gradient Based Algorithm," Journal of Artificial Intelligence Research 74 (2022) 1565-1597, Aug 2022.
[J118] Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, Nicolo Michelusi, Vaneet Aggarwal, David J. Love, Huaiyu Dai, "Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks," IEEE/ACM Transactions on Networking, vol. 30, no. 4, pp. 1569-1584, Aug. 2022, doi: 10.1109/TNET.2022.3143495.
[J117] Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli, "Multi-Agent Multi-Armed Bandits with Limited Communication," Journal of Machine Learning Research, Jul 2022.
[J116] Ashutosh Singh, Abubakr Alabbasi, and Vaneet Aggarwal, "A Distributed Model-Free Algorithm for Multi-hop Ride-sharing using Deep Reinforcement Learning," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 8595-8605, July 2022, doi: 10.1109/TITS.2021.3083740.
[J115] Yimeng Wang, Mridul Agarwal, Tian Lan, and Vaneet Aggarwal, "Learning-based Online QoE Optimization in Multi-Agent Video Streaming," Algorithms, 15(7), 227, Jun 2022.
[J114] Kaushik Manchella, Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "PassGoodPool: Joint Passengers and Goods Fleet Management with Reinforcement Learning aided Pricing, Matching, and Route Planning," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 4, pp. 3866-3877, April 2022, doi: 10.1109/TITS.2021.3128877.
[J113] Guoyang Zhou, Vaneet Aggarwal, Ming Yun, and Denny Yu, "A Computer Vision Approach for Estimating Lifting Load Contributors to Injury Risk," IEEE Transactions on Human-Machine Systems, vol. 52, no. 2, pp. 207-219, April 2022, doi: 10.1109/THMS.2022.3148339.
[J112] Abubakr Alabassi and Vaneet Aggarwal, "Joint Information Freshness and Completion Time Optimization for Vehicular Networks," IEEE Transactions on Services Computing, vol. 15, no. 2, pp. 1118-1129, 1 March-April 2022, doi: 10.1109/TSC.2020.2978063
[J111] Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, and Satish V. Ukkusuri, "On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)," Journal of Machine Learning Research, vol. 23 no. 129, pp.1-46, Mar 2022.
[J110] Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "AdaPool: A Diurnal-Adaptive Fleet Management Framework using Model-Free Deep Reinforcement Learning and Change Point Detection," IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2471-2481, March 2022, doi: 10.1109/TITS.2021.3109611.
[J109] Mridul Agarwal, Vaneet Aggarwal, Arnob Ghosh, Nilay Tiwari, "Reinforcement Learning for Mean Field Game," Algorithms, Feb 2022.
[J108] Mahadesh Panju, Ramkumar Raghu, Vinod Sharma, Vaneet Aggarwal, and Rajesh Ramachandran,"Queueing Theoretic Models for Uncoded and Coded Multicast Wireless Networks with Caches," IEEE Transactions on Wireless Communications, vol. 21, no. 2, pp. 1257-1271, Feb. 2022, doi: 10.1109/TWC.2021.3103422
[J107] Amrit Singh Bedi, Ketan Rajawat, Vaneet Aggarwal, and Alec Koppel, "Escaping Saddle Points for Successive Convex Approximation," in IEEE Transactions on Signal Processing, vol. 70, pp. 307-321, Jan 2022, doi: 10.1109/TSP.2021.3138242.
[J106] Ajay Kumar Badita, Parimal Parag, and Vaneet Aggarwal, “Single-forking of coded subtasks for straggler mitigation,” IEEE/ACM Transactions on Networking, vol. 29, no. 6, pp. 2413-2424, Dec. 2021, doi: 10.1109/TNET.2021.3075377.
[J105] Marina Haliem, Ganapathy Mani, Vaneet Aggarwal, and Bharat Bhargava, "A Distributed Model-Free Ride-Sharing Approach for Joint Matching, Pricing, and Dispatching using Deep Reinforcement Learning," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 12, pp. 7931-7942, Dec. 2021, doi: 10.1109/TITS.2021.3096537.
[J104] Guanghui Zhang, Jack Y. B. Lee, Ke Liu, Haibo Hu, and Vaneet Aggarwal, "A Unified Framework for Flexible Playback Latency Control in Live Video Streaming," IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 12, pp. 3024-3037, 1 Dec. 2021, doi: 10.1109/TPDS.2021.3083202.
[J103] Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, and Abhishek Umrawal, "Stochastic Top K-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization," ACM/IMS Transactions on Data Science, vol. 2, issue 4, Article 38, Nov 2021, DOI:https://doi.org/10.1145/3507787.
[J102] Ramkumar Raghu, Pratheek Upadhyaya, Mahadesh Panju, Vaneet Aggarwal, and Vinod Sharma, "Scheduling and Power Control for Wireless Multicast Systems via Deep Reinforcement Learning," Entropy, Nov 2021; 23(12):1555. https://doi.org/10.3390/e23121555.
[J101] Vaneet Aggarwal, Tian Lan, and Dheeraj Peddireddy, "Preemptive Scheduling on Unrelated Machines with Fractional Precedence Constraints," Journal of Parallel and Distributed Computing, Volume 157, November 2021, Pages 280-286.
[J100] Rutvij H. Jhaveri, Sagar V. Ramani, Gautam Srivastava, Thippa Reddy Gadekallu, and Vaneet Aggarwal, "Fault-Resilience for Bandwidth Management in Industrial Software-Defined Networks," IEEE Transactions on Network Science and Engineering, vol. 8, no. 4, pp. 3129-3139, 1 Oct.-Dec. 2021, doi: 10.1109/TNSE.2021.3104499.
[J99] Abubakr Alabbasi, Vaneet Aggarwal, Tian Lan, Yu Xiang, Moo-Ryong Ra, and Yih-Farn R. Chen, "FastTrack: Minimizing Stalls for CDN-based Over-the-top Video Streaming Systems," IEEE Transactions on Cloud Computing, vol. 9, no. 4, pp. 1453-1466, Oct.-Dec. 2021, doi: 10.1109/TCC.2019.2920979
[J98] Mridul Agarwal and Vaneet Aggarwal, "Blind Decision Making: Reinforcement Learning with Delayed Observations," Pattern Recognition Letters, Volume 150, October 2021, Pages 176-182.
[J97] Yang Zhang, Arnob Ghosh, and Vaneet Aggarwal, "Optimized Portfolio Contracts for Bidding the Cloud," IEEE Transactions on Service Computing, vol. 14, no. 5, pp. 1505-1518, 1 Sept.-Oct. 2021, doi: 10.1109/TSC.2018.2886885.
[J96] Vaneet Aggarwal, Tian Lan, Suresh Subramaniam, Maotong Xu, "On the Approximability of Related Machine Scheduling under Arbitrary Precedence," IEEE Transactions on Network and Service Management, vol. 18, no. 3, pp. 3706-3718, Sept. 2021, doi: 10.1109/TNSM.2021.3072296.
[J95] Fanglin Bao, Hyunsoo Choi, Vaneet Aggarwal, Zubin Jacob, "Quantum-accelerated imaging of N stars," Optics Letters, Vol. 46, Issue 13, pp. 3045-3048, Jul 2021, DOI: 10.1364/OL.430404 (Highlighted as an Editor's Pick).
[J94] Naimahmed Nesaragi, Shivnarayan Patidar, and Vaneet Aggarwal, "Tensor Learning of Pointwise Mutual Information from EHR Data for Early Prediction of Sepsis," Computers in Biology and Medicine, Volume 134, July 2021, 104430.
[J93] Ruijiu Mao and Vaneet Aggarwal, "NPSCS: Non-preemptive Stochastic Co-flow Scheduling with Time-Indexed LP Relaxation," IEEE Transactions of Networking and Service Management, vol. 18, no. 2, pp. 2377-2387, Jun 2021, DOI: 10.1109/TNSM.2021.3051657.
[J92] Kaushik Manchella, Abhishek K. Umrawal, and Vaneet Aggarwal, "FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers and Goods Transportation," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2035-2047, April 2021, doi: 10.1109/TITS.2020.3048361.
[J91] Dheeraj Peddireddy, Xingyu Fu, Anirudh Shankar, Haobo Wang, Byung Gun Joung, Vaneet Aggarwal, John W. Sutherland, and Martin Byung-Guk Jun, "Identifying Manufacturability and Machining Processes using Deep 3D Convolutional Networks," Journal of Manufacturing Processes, vol. 64, pp. 1336-1348, Apr 2021.
[J90] Abubakr Al-Abbasi and Vaneet Aggarwal, "VidCloud: Joint Stall and Quality Optimization for Video Streaming over Cloud," ACM Transactions on Modeling and Performance Evaluation of Computing Systems, article no. 17, Jan 2021, https://doi.org/10.1145/3442187
[J89] Anis Elgabli, Jihong Park, Amrit S. Bedi, Chaouki Ben Issaid, Mehdi Bennis, and Vaneet Aggarwal, "Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning," IEEE Transactions on Communications, vol. 69, no. 1, pp. 164-181, Jan 2021, doi: 10.1109/TCOMM.2020.3026398.
[J88] Krishnandu Hazra, Vijay Shah, Simone Silvestri, Vaneet Aggarwal, Sajal Das, Subrata Nandi, Sujoy Saha, "Designing Efficient Communication Infrastructure in Post-disaster Situations with Limited Availability of Network Resources," Computer Communications, Volume 164, Pages 54-68, Dec 2020.
[J87] Md Masudur Rahman, Mythra Varun Balakuntala Srinivasa Mur, Mridul Agarwal, Upinder Kaur, Vishnunandan Lakshmi Venkatesh, Glebys Gonzalez, Natalia Sanchez Tamayo, Yexiang Xue, Richard Voyles, Vaneet Aggarwal, and Juan Wachs, "SARTRES: A Semi-Autonomous Robot TeleopeRation Environment for Surgery," AE-CAI 2020 Special Issue of the Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Journal (TCIV), Nov 2020, DOI: 10.1080/21681163.2020.1834878.
[J86] Abubakr O. Alabbasi and Vaneet Aggarwal, "TTLCache: Taming Latency in Erasure-Coded Storage Through TTL Caching," IEEE Transactions on Network and Service Management, vol. 17, no. 3, pp. 1582-1596, Sept. 2020, doi: 10.1109/TNSM.2020.2998175.
[J85] Shanuja Sasi, V. Lalitha, Vaneet Aggarwal, and B. Sundar Rajan, "Straggler Mitigation with Tiered Gradient Codes," IEEE Transactions on Communications, vol. 68, no. 8, pp. 4632-4647, Aug. 2020, doi: 10.1109/TCOMM.2020.2992721.
[J84] Arnob Ghosh, Vaneet Aggarwal, and Prakash Chakraborty, "Tiered Spectrum Measurement Markets for joint Licensed and Unlicensed Secondary Access," IEEE Transactions on Network Science and Engineering, vol. 7, no. 3, pp. 1295-1309, 1 July-Sept. 2020, doi: 10.1109/TNSE.2019.2921782.
[J83] Anis Elgabli and Vaneet Aggarwal, "FastScan: Robust Low-Complexity Rate Adaptation Algorithm for Video Streaming over HTTP," IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 7, pp. 2240-2249, July 2020.
[J82] Morteza Ashraphijuo, Xiaodong Wang, and Vaneet Aggarwal, "Fundamental sampling patterns for low-rank multi-view data completion," Pattern Recognition, vol. 103, Jul 2020.
[J81] Ke Liu, Zhongbin Zha, Wenkai Wan, Vaneet Aggarwal, Binzhang Fu, and Mingyu Chen, "Optimizing TCP Loss Recovery Performance Over Mobile Data Networks," IEEE Transactions on Mobile Computing, vol. 19, no. 6, pp. 1401-1419, June 2020.
[J80] Ajay Badita, Parimal Parag, and Vaneet Aggarwal, "Optimal Server Selection for Straggler Mitigation," IEEE/ACM Transactions on Networking, vol. 28, no. 2, pp. 709-721, April 2020.
[J79] Hamed Asadi, Guoyang Zhou, Jae Joong Lee, Vaneet Aggarwal, and Denny Yu, "A Computer Vision Algorithm to Identify High Force Exertions from Facial Expressions," Ergonomics, Apr 2020.
[J78] Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis, and Vaneet Aggarwal,"GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning," Journal of Machine Learning Research, Mar 2020.
[J77] Xiao-Yang Liu, Shuchin Aeron, Vaneet Aggarwal, and Xiaodong Wang, "Low-tubal-rank Tensor Completion using Alternating Minimization," IEEE Transactions on Information Theory, vol. 66, no. 3, pp. 1714-1737, March 2020.
[J76] Arnob Ghosh and Vaneet Aggarwal, "Penalty Based Control Mechanism for Strategic Prosumers in a Distribution Network," Energies, Special Issue Smart Management of Distributed Energy Resources, 13(2), 452, Jan 2020.
[J75] Anis Elgabli, Ke Liu, and Vaneet Aggarwal, "Optimized Preference-Aware Multi-path Video Streaming with Scalable Video Coding," IEEE Transactions on Mobile Computing, vol. 19, no. 1, pp. 159-172, 1 Jan. 2020.
[J74] Vaneet Aggarwal and Ruijiu Mao, "Preemptive Scheduling for Approximate Computing on Heterogeneous Machines: Tradeoff between Weighted Accuracy and Makespan," Information Processing Letters, Volume 153, January 2020.
[J73] Abubakr Al-Abbasi, Arnob Ghosh, and Vaneet Aggarwal, "DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning," IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 12, pp. 4714-4727, Dec. 2019.
[J72] Yimeng Wang, Yongbo Li, Tian Lan, and Vaneet Aggarwal, "DeepChunk: Deep Q-Learning for Chunk-based Caching in Data Processing Networks," IEEE Transactions on Cognitive Communications and Networking, Special Issue on Deep Reinforcement Learning for Future Wireless Communication Networks, vol. 5, no. 4, pp. 1034-1045, Dec. 2019.
[J71] Chinmayananda Arunachala, Vaneet Aggarwal, and B. Sundar Rajan, ``On the Optimal Broadcast Rate of the Two-Sender Unicast Index Coding Problem with Fully-Participated Interactions," IEEE Transactions on Communications, vol. 67, no. 12, pp. 8612-8623, Dec. 2019.
[J70] Abubakr Alabbasi, Vaneet Aggarwal, and Tian Lan, "TTLoC: Taming Tail Latency for Erasure-coded Cloud Storage Systems," IEEE Transactions on Network and Service Management, vol. 16, no. 4, pp. 1609-1623, Dec. 2019.
[J69] Ashwin Kumar Boddeti, Abubakr Alabbasi, Vaneet Aggarwal, and Zubin Jacob, "Spectral domain inverse design for accelerating nanocomposite metamaterials discovery," Optical Materials Express, Vol. 9, Issue 12, pp. 4765-4771, Dec 2019.
[J68] Tianqiong Luo, Vaneet Aggarwal, and Borja Peleato, "Coded caching with distributed storage," IEEE Transactions on Information Theory, vol. 65, no. 12, pp. 7742-7755, Dec. 2019.
[J67] Fernando Stefanello, Vaneet Aggarwal, Luciana S. Buriol, and Mauricio G.C. Resende, "Hybrid Algorithms for Placement of Virtual Machines across Geo-Separated Data Centers," Journal of Combinatorial Optimization, Volume 38, Issue 3, pp 748–793, Oct 2019.
[J66] Morteza Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "Deterministic and Probabilistic Conditions for Finite Completability of Low-Tucker-Rank Tensor," IEEE Transactions on Information Theory, vol. 65, no. 9, pp. 5380-5400, Sept. 2019.
[J65] Anis Elgabli, Muhamad Felemban, and Vaneet Aggarwal, "GiantClient: Video HotSpot for Multi-User Streaming," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 9, pp. 2833-2843, Sept. 2019.
[J64] Eric Friedlander and Vaneet Aggarwal, "Generalization of LRU Cache Replacement Policy with Applications to Video Streaming," ACM Tompecs, Volume 4 Issue 3, August 2019.
[J63] Arnob Ghosh, Vaneet Aggarwal, and Hong Wan, "Strategic Prosumers: How to set the prices Dynamically in a Tiered Market?," IEEE Transactions on Industrial Informatics, vol. 15, no. 8, pp. 4469-4480, Aug. 2019
[J62] Anis Elgabli and Vaneet Aggarwal, "SmartStreamer: Preference-Aware Multipath Video Streaming over MPTCP," IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6975-6984, July 2019.
[J61] Chinmayananda Arunachala, Vaneet Aggarwal, and B. Sundar Rajan, "Optimal Linear Broadcast Rates of Some Two-Sender Unicast Index Coding Problems," IEEE Transactions on Communications, vol. 67, no. 6, pp. 3965-3977, June 2019.
[J60] Anis Elgabli, Muhamad Felemban, and Vaneet Aggarwal, "GroupCast: Preference-Aware Cooperative Video Streaming with Scalable Video Coding," IEEE/ACM Transactions on Networking, vol. 27, no. 3, pp. 1138-1150, June 2019.
[J59] Anis Elgabli, Ali Elghariani, Vaneet Aggarwal, and Mark Bell, "A Low Complexity Detection Algorithm For Uplink Massive MIMO Systems Based on Alternating Minimization," IEEE Wireless Communications Letters, vol. 8, no. 3, pp. 917-920, June 2019.
[J58] Yu Xiang, Vaneet Aggarwal, Tian Lan, and Yih-Farn Robin Chen, "Differentiated latency in data center networks with erasure coded files through traffic engineering," IEEE Transactions on Cloud Computing, vol. 7, no. 2, pp. 495-508, 1 April-June 2019.
[J57] Anis Elgabli and Vaneet Aggarwal, "Deadline And Buffer Constrained Knapsack Problem," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 5, pp. 1564-1568, May 2019.
[J56] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Principal Component Analysis with Tensor Train Subspace," Pattern Recognition Letters, vol. 122, pp. 86-91, May 2019.
[J55] Abubakr Alabbasi, Vaneet Aggarwal, and Moo-Ryong Ra, "Multi-tier Caching Analysis in CDN-based Over-the-top Video Streaming Systems," IEEE/ACM Transactions on Networking, vol. 27, no. 2, pp. 835-847, April 2019.
[J54] Yang Zhang, Arnob Ghosh, Vaneet Aggarwal, and Tian Lan, "Tiered cloud storage pricing via two-stage, latency-aware bidding," IEEE Transactions on Network and Service Management, vol. 16, no. 1, pp. 176-191, March 2019.
[J53] Zijian He, Vaneet Aggarwal, and Shimon Y. Nof, "Differentiated Service Policy in Smart Warehouse Automation," International Journal of Production Research, vol. 56, no. 22, pp. 6956-6970, 2018.
[J52] Arnob Ghosh, Randall Berry, and Vaneet Aggarwal, "Spectrum Measurement Markets for Tiered Spectrum Access," IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 4, pp. 929-941, Dec. 2018.
[J51] Arnob Ghosh and Vaneet Aggarwal, "Menu-Based Pricing for Charging of Electric Vehicles with Vehicle-to-Grid Service," IEEE Transactions on Vehicular Technology, vol. 67, no. 11, pp. 10268-10280, Nov. 2018.
[J50] Arnob Ghosh and Vaneet Aggarwal, "Control of Charging of Electric Vehicles through Menu-Based Pricing," IEEE Transactions on Smart Grid, vol. 9, no. 6, pp. 5918-5929, Nov. 2018.
[J49] Dixita Limbachia, Manish Gupta, and Vaneet Aggarwal, "Family of Constrained Codes for Archival DNA Data Storage," IEEE Communications Letters, vol. 22, no. 10, pp. 1972-1975, Oct. 2018.
[J48] Milad Rezaee, Mahtab Mirmohseni, Vaneet Aggarwal, and Mohammad Reza Aref, "Optimal Transmission Policies for Multi-hop Energy Harvesting Systems," IEEE Transactions on Green Communications and Networking, vol. 2, no. 3, pp. 751-763, Sept. 2018.
[J47] Abubakr Alabassi and Vaneet Aggarwal, "Video Streaming in Distributed Erasure-coded Storage Systems: Stall Duration Analysis," IEEE/ACM Transactions on Networking, vol. 26, no. 4, pp. 1921-1932, Aug. 2018.
[J46] Anis Elgabli, Vaneet Aggarwal, Shuai Hao, Feng Qian, and Subhabrata Sen, "LBP: Robust Rate Adaptation Algorithm for SVC Video Streaming," IEEE/ACM Transactions on Networking, vol. 26, no. 4, pp. 1633-1645, Aug. 2018.
[J45] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Tensor Train Neighborhood Preserving Embedding," IEEE Transactions on Signal Processing, vol. 66, no. 10, pp. 2724-2732, May, 2018.
[J44] Morteza Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On Deterministic Sampling Patterns for Robust Low-Rank Matrix Completion," IEEE Signal Processing Letters, vol. 25. no. 3, pp. 343-347, Mar 2018.
[J43] Vaneet Aggarwal, Zhe Wang, Xiaodong Wang, and Muhammad Ismail, "Energy Scheduling for Optical Channels with Energy Harvesting Devices," IEEE Transactions on Green Communications and Networking, vol. 2, no. 1, pp. 154-162, Mar 2018.
[J42] Vaneet Aggarwal, Yih-Farn Robin Chen, Tian Lan, and Yu Xiang, "Sprout: A functional caching approach to minimize service latency in erasure-coded storage," IEEE/ACM Transactions on Networking, vol. 25, no. 6, pp. 3683-3694, Dec 2017.
[J41] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Unsupervised Clustering Under The Union of Polyhedral Cones (UOPC) Model," Pattern Recognition Letters, vol. 100, pp. 104-109, Dec 2017 [Code available on github].
[J40] Vaneet Aggarwal, Mark R. Bell, Anis Elgabli, Xiaodong Wang, and Shan Zhong, "Joint Energy- Bandwidth Allocation for Multi-User Channels with Cooperating Hybrid Energy Nodes," IEEE Transactions on Vehicular Technology, vol. 66, no. 11, pp. 9880-9889, Nov. 2017.
[J39] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "The DoF of Two-way Butterfly Networks," IEEE Communications Letters, vol. 21, no. 10, pp. 2254-2257, Oct 2017.
[J38] Morteza Ashraphijuo, Xiaodong Wang, and Vaneet Aggarwal, "Rank Determination for Low-Rank Data Completion," Journal of Machine Learning Research, vol. 18(98), pp. 1-29, Sept 2017.
[J37] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the DoF of Two-way 2x2x2 Relay Networks with or without Relay Caching," IET Communications, Volume 11, Issue 13, pp. 2089 – 2094, Sept 2017.
[J36] Alireza Vahid, Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "Interference management with mismatched partial channel state information," EURASIP Journal on Wireless Communications and Networking, Aug 2017.
[J35] Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Optimizing Differentiated Latency in Multi-Tenant, Erasure-Coded Storage," IEEE Transactions on Network and Service Management, vol. 14, no. 1, pp. 204-216, March 2017.
[J34] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Symmetric K-user Interference Channels with Limited Feedback," IEEE Trans. Inf. Th., vol. 62, no. 12, pp. 6969-6985, Dec. 2016.
[J33] Vaneet Aggarwal and Lauren Huie, "Antenna Placement in MIMO Radar-Based Systems with different quality receive antennas," IEEE Signal Processing Letters, vol. 23, no. 12, pp. 1732-1735, Dec 2016.
[J32] Xiao-Yang Liu, Shuchin Aeron, Vaneet Aggarwal, Xiaodong Wang, and Min-You Wu, "Adaptive Sampling of RF fingerprints for Fine-grained Indoor Localization," IEEE Transactions on Mobile Computing, vol. 15, no. 10, pp. 2411-2423, Oct. 2016.
[J31] Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Joint Latency and Cost Optimization for Erasure-coded Data Center Storage," IEEE/ACM Transactions on Networking, vol. 24, no. 4, pp. 2443-2457, Aug. 2016.
[J30] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Optimal Energy-Bandwidth Allocation for Energy-Harvesting Networks in Multiuser Fading Channels," IEEE Journal on Selected Areas in Communications, vol. 34, no. 5, pp. 1565-1577, May 2016.
[J29] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Transmission with Energy Harvesting Nodes in Frequency-Selective Fading Channels," IEEE Transactions on Wireless Communications, vol. 15, no. 3, pp. 1642-1656, March 2016.
[J28] Pedro Santacruz, Vaneet Aggarwal, and Ashutosh Sabharwal, "Leveraging Physical Layer Capabilities: Distributed Scheduling in Interference Networks with Local Views," IEEE/ACM Transactions on Networking, vol. 24, no. 1, pp. 368-382, Feb. 2016.
[J27] Robert Margolies, Ashwin Sridharan, Vaneet Aggarwal, Ritwik Jana, N.K. Shankaranarayanan, Vinay Vaishampayan, and Gil Zussman, "Exploiting Mobility in Proportional Fair Cellular Scheduling: Measurements and Algorithms," IEEE/ACM Transactions on Networking, vol. 24, no. 1, pp. 355-367, Feb. 2016.
[J26] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Capacity of Energy Harvesting Communication Link," IEEE Journal on Selected Areas in Communications, vol. 33, no. 12, pp. 2671-2686, Dec. 2015.
[J25] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Capacity of Two-Way Diamond Channel," IEEE Trans. Inf. Th., vol. 61, no. 11, pp. 6060-6090, Nov. 2015.
[J24] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Joint Energy-Bandwidth Allocation in Multiple Broadcast Channels with Energy Harvesting," IEEE Transactions on Communications, vol. 63, no. 10, pp. 3842-3855, Oct. 2015.
[J23] Chao Tian, Birenjith Sasidharan, Vaneet Aggarwal, Vinay Vaishampayan, and P. Vijay Kumar, "Layered, Exact-Repair Regenerating Codes Via Embedded Error Correction and Block Designs," IEEE Trans. Inf. Th., vol.61, no.4, pp.1933-1947, April 2015.
[J22] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Iterative Dynamic Waterfilling for Fading Multiple-Access Channels with Energy Harvesting," IEEE J-SAC Special Issue on Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer, vol.33, no.3, pp.382-395, Mar 2015
[J21] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Power Allocation for Energy Harvesting Transmitter with Causal Information," IEEE Transactions on Communications, vol.62, no.11, pp.4080- 4093, Nov. 2014.
[J20] Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Joint Latency and Cost Optimization for Erasure-coded Data Center Storage," ACM SIGMETRICS Performance Evaluation Review, vol, 42, no. 2, pp.3-14, Sept. 2014.
[J19] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Capacity and Degrees of Freedom Regions of Two-User MIMO Interference Channels with Limited Receiver Cooperation," IEEE Trans. Inf. Th., vol.60, no.7, pp.4170-4196, July 2014
[J18] Melissa Duarte, Ashutosh Sabharwal, Vaneet Aggarwal, Rittwik Jana, Kadangode Ramakrishnan, Chris Rice, and N. K. Shankar, "Design and Characterization of a Full-duplex Multi-antenna System for WiFi networks," IEEE Transactions on Vehicular Tech., vol.63, no.3, pp.1160-1177, March 2014. (2017 Jack Neubauer Memorial Award recognizing the Best Systems Paper published in the IEEE Transactions on Vehicular Technology)
[J17] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Capacity Region and the Generalized Degrees of Freedom Region for MIMO Interference Channel with Feedback," IEEE Trans. Inf. Th., vol. 59, no. 12, pp.8357-8376, Dec. 2013.
[J16] Vaneet Aggarwal, and N.K. Shankaranarayan, "Performance of a Random-Access Wireless Network with a Mix of Full- and Half-Duplex Stations," IEEE Trans. Communication Letters, vol. 17, no. 11, pp.2200-2203, Nov. 2013.
[J15] Achaleshwar Sahai, Vaneet Aggarwal, Melda Yuksel and Ashutosh Sabharwal, "Capacity of All Nine Models of Channel Output Feedback for the Two-User Interference Channel," IEEE Transactions on Information Theory, vol. 59, no. 11, pp. 6957-6979, Nov 2013.
[J14] Vaneet Aggarwal, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan and Vinay Vaishampayan, "Improved Cloud Resource Utilization for IPTV Transmission," R-letters, vol. 4, no. 4, pp. 13-14, Aug. 2013.
[J13] Vaneet Aggarwal, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan and Vinay Vaishampayan, "Optimizing Cloud Resources for Delivering IPTV Services through Virtualization," IEEE Transactions on Multimedia, special issue on Cloud-Based Mobile Media: Infrastructure, Services, vol. 15, no. 4, pp. 789-801, June 2013
[J12] Vaneet Aggarwal, Youjian Liu and Ashutosh Sabharwal, "Sum-capacity of Interference Channels with a Local View: Impact of Distributed Decisions," IEEE Trans. Information Theory, vol. 48(3), pp. 1630-1659, Mar 2012.
[J11] Satashu Goel, Vaneet Aggarwal, Aylin Yener and Robert Calderbank, "The Effect of Eavesdroppers on Network Connectivity: A Secrecy Graph Approach," IEEE Transactions on Information Forensics & Security, vol. 6(3), pp. 712-724, Sept 2011.
[J10] Vaneet Aggarwal and Ashutosh Sabharwal, "Bits About the Channel: Multi-round Protocols for Two-way Fading Channels," IEEE Trans. Information Theory, vol. 57(6), pp. 3352-3370, June 2011.
[J9] Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "On Achieving Local View Capacity Via Maximal Independent Graph Scheduling," Special Issue of the IEEE Transactions on Information Theory on Interference Networks, vol. 57(5), pp. 2711-2729, May 2011.
[J8] Vaneet Aggarwal, A. Robert Calderbank, Gerald Gilbert and Yaakov S. Weinstein, "Volume Thresholds for Quantum Fault Tolerance," Quantum Information Processing, pp. 541-549, Oct. 2010.
[J7] Vaneet Aggarwal and Ashutosh Sabharwal, "Power-Controlled Training and Feedback for Two-way MIMO Channels," IEEE Trans. Information Theory, vol.56, no.7, pp.3310-3331, July 2010.
[J6] Vaneet Aggarwal, Lalitha Sankar, A. Robert Calderbank, and H. Vincent Poor, "Secrecy capacity of a class of orthogonal relay eavesdropper channels," EURASIP special issue on Wireless Physical Layer Security, Jul. 2009.
[J5] Amir Bennatan, Vaneet Aggarwal, Yiyue Wu, A. Robert Calderbank, Jacob Hoydis and Aik Chindapol, "Bounds and Lattice-Based Transmission Strategies for the Phase-Faded Dirty-Paper Channel," IEEE Trans. Wireless Communications, vol. 8(7), pp. 3620-3627, Jul. 2009.
[J4] Vaneet Aggarwal, Amir Bennatan, and A. Robert Calderbank, "On Maximizing Coverage in Gaussian Relay Channels", IEEE Trans. Information Theory, vol.55, no.6, pp. 2518-2536, Jun. 2009.
[J3] Vaneet Aggarwal and Ashutosh Sabharwal, "Performance of Multiple Access Channels with Asymmetric Feedback," IEEE Journal on Selected Areas in Communications, vol.26, no.8, pp. 1516-1525, Oct 2008.
[J2] Vaneet Aggarwal and A. Robert Calderbank, "Boolean Functions, Projection Operators, and Quantum Error Correcting Codes," IEEE Trans. Information Theory, vol.54, no.4, pp.1700-1707, Apr 2008.
[J1] Vaneet Aggarwal and Ashutosh Sabharwal, "Slotted Gaussian Multiple Access Channel: Stable Region and Impact of Side Information," EURASIP special issue on Theory and Applications in Multiuser/Multiterminal Communications, Apr 2008.
Other Conference Publications (<7 pages or non-Core-A*/A):
[C118] Hanhan Zhou, Tian Lan, and Vaneet Aggarwal, "Double Policy Estimation for Importance Sampling in Sequence Modeling-Based Reinforcement Learning," NeurIPS Foundation Models for Decision Making Workshop, Dec 2023
[C117] Abhishek Kumar Umrawal, Vaneet Aggarwal, and Christopher J. Quinn, "Fractional Budget Allocation for Influence Maximization," IEEE Conference on Decision and Control (CDC), Dec 2023.
[C116] Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, and Vaneet Aggarwal, "Combinatorial Stochastic-Greedy Bandit," Sixteenth European Workshop on Reinforcement Learning, Sept 2023.
[C115] Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangia, and Vaneet Aggarwal, "A Shallow Hybrid Classical-Quantum Spiking Feedforward Neural Network for Noise-Robust Image Classification," IEEE International Joint Conference on Neural Networks (IJCNN), Jun 2023
[C114] Jiaqi Yao, Ke Liu, Ting Liang, Theophilus Benson, Jack Y. B. Lee, Vaneet Aggarwal, Yungang Bao, and Mingyu Chen, "A Data-Driven Framework for TCP to Achieve Flexible QoS Control in Mobile Data Networks," IEEE/ACM International Symposium on Quality of Service 2023 (IWQoS 2023), Jun 2023
[C113] Xingyu Fu, Dheeraj Peddireddy, Fengfeng Zhou, Yuting Xi, Vaneet Aggarwal, Xingyu Li, and Martin Jun, "BREP Compatible Feature Recognition for Manufacturing CAD Models," 51st SME North American Manufacturing Research Conference, Jun 2023.
[C112] Abhishek K. Umrawal and Vaneet Aggarwal, "Leveraging the Community Structure of a Social Network for Maximizing the Spread of Influence," ACM SIGMETRICS Performance Evaluation Review. 2023 Apr 27;50(4):17-19 (Sigmetrics 2022 Poster)
[C111] Rooji Jinan, Gaurav Gautam, Parimal Parag, and Vaneet Aggarwal, "Asymptotic Analysis of Probabilistic Scheduling for Erasure-Coded Heterogeneous Systems," ACM SIGMETRICS Performance Evaluation Review. 2023 Apr 27;50(4):8-10 (Sigmetrics 2022 Poster)
[C110] Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, and Vaneet Aggarwal, "Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming," CDC, Dec 2022.
[C109] Jiayu Chen, Jingdi Chen, Tian Lan, and Vaneet Aggarwal, "Multi-agent Covering Option Discovery through Kronecker Product of Factor Graphs," in Proc. AAMAS, May 2022 (40% acceptance rate, 257/629).
[C108] Bhargav Ganguly, Marina Haliem, Mridul Agarwal, Vaneet Aggarwal, and Bharat Bhargava, "Decision making without prior knowledge in dynamic environments using Bootstrapped DQN," in Proc. AAAI 2022 Spring Symposia, Feb 2022
[C107] Trevor Bonjour, Vaneet Aggarwal, and Bharat Bhargava, "Information-Theoretic Approach to Detect Collusion in Multi-Agent Games," in Proc. AAAI 2022 Spring Symposia, Feb 2022
[C106] Abhishek Kumar Umrawal and Vaneet Aggarwal, "Community-IM: A Community-based Algorithm for Social Influence Maximization," in Proc. AAAI Workshop on Graphs and More Complex Structures for Learning and Reasoning (GCLR), Feb 2022.
[C105] Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, and Satish Ukkusuri, "On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)," in Proc. Neurips Workshop on Cooperative AI, Dec. 2021 (Best paper award)
[C104] Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Identification of Latent Graphs: A Quantum Entropic Approach," in Proc. Neurips Workshop on Causal Inference & Machine Learning WHY-21, Dec. 2021
[C103] Dheeraj Pedirredy, Vipul Bansal, Zubin Jacob, and Vaneet Aggarwal, "Tensor Ring Parametrized Variational Quantum Circuits for Large Scale Quantum Machine Learning," in Proc. Neurips Workshop on Quantum Tensor Networks in Machine Learning, Dec. 2021
[C102] Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, "Tensor Rings for Learning Circular Hidden Markov Models," in Proc. Neurips Workshop on Quantum Tensor Networks in Machine Learning, Dec. 2021
[C101] Anis Elgabli, Chaouki Ben Issaid, Amrit S. Bedi, Mehdi Bennis, and Vaneet Aggarwal, "Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent," in Proc. IEEE Globecom, Dec 2021
[C100] Alec Koppel, Amrit Bedi, Bhargav Ganguly, and Vaneet Aggarwal, “Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning,” in Proc. Asilomar, Nov 2021.
[C99] Guoyang Zhou, Vaneet Aggarwal, Ming Yin, and Denny Yu, ``Video-Based AI Decision Support System for Lifting Risk Assessment," in Proc. IEEE SMC, Oct. 2021
[C98] Mridul Agarwal, Glebys Gonzalez, Mythra Varun Balakuntala Srinivasa Murthy, Md Masudur Rahman, Vaneet Aggarwal, Yexiang Xue, Juan Wachs, Richard Voyles,"Dexterous Skill Transfer between Surgical Procedures for Teleoperated Robotic Surgery," in Proc. 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), Aug 2021.
[C97] Mridul Agarwal and Vaneet Aggarwal, "Blind Decision Making: Reinforcement Learning with Delayed Observations," in Proc. ICAPS, Aug 2021.
[C96] Mohammad Ali Javidian, Vaneet Aggarwal, and Zubin Jacob, “Quantum Causal Inference: an Entropic Approach,” in Proc. UAI Workshop, Jul 2021
[C95] Jiayu Chen, Marina Haliem, Tian Lan, and Vaneet Aggarwal, "Multi-agent Deep Covering Option Discovery," in Proc. ICML Reinforcement Learning for Real Life Workshop, Jul 2021.
[C94] Servio Palacios, Drew Zabrocki, Bharat Bhargava, and Vaneet Aggarwal, "Auditable Serverless Computing for Farm Management," International Workshop on Big Data in Emergent Distributed Environments (BiDEDE), Jun 2021.
[C93] Shanuja Sasi, Vaneet Aggarwal, and B. Sundar Rajan, "An Embedded Index Code Construction Using Sub-packetization," in Proc. IEEE Information Theory Workshop (ITW), Apr 2021 (Extended Version).
[C92] Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "Novelty Detection and Adaptation: A Domain Agnostic Approach," in Proc. International Semantic Intelligence Conference (ISIC 2021), Feb 2021.
[C91] Kaushik Manchella, Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "A Distributed Delivery-Fleet Management Framework using Deep Reinforcement Learning and Dynamic Multi-Hop Routing," in Proc. Neurips Workshop on Machine Learning for Autonomous Driving, Dec 2020 (video).
[C90] Yifan Shen, Ke Liu, Ziting Guo, Wenli Zhang, Guanghui Zhang, Mingyu Chen and Vaneet Aggarwal, "Freeway: An Order-Less User-Space Framework for Non-Real-Time Applications," in Proc. IEEE International Conference on High Performance Computing and Communications (HPCC), Dec 2020 (15% acceptance rate, 58/379).
[C89] Marina Haliem, Ganapathy Mani, Vaneet Aggarwal, and Bharat Bhargava, "Distributed Model-Free Ride-Sharing Algorithm with Pricing using Deep Reinforcement Learning," in Proc. ACM Computer Science in Cars Symposium (CSCS), Dec 2020
[C88] Mayank Gupta, Lingjun Chen, Denny Yu, and Vaneet Aggarwal, "A Supervised Learning Approach for Robust Health Monitoring using Face Videos," in Proc. 2nd ACM Workshop on Device Free Human Sensing (DFHS, ACM Buildsys Workshop), Nov. 2020
[C87] Marina Haliem, Vaneet Aggarwal, and Bharat Bhargava, "AdaPool: An Adaptive Model-Free Ride-Sharing Approach for Vehicle Dispatching using Deep Reinforcement Learning," in Proc. ACM Buildsys, Nov. 2020
[C86] Divija Swetha Gadiraju, V. Lalitha, and Vaneet Aggarwal, "Secure Regenerating Codes for Reducing Storage and Bootstrap Costs in Sharded Blockchains," in Proc. IEEE International Conference on Blockchain, Nov 2020 (16% acceptance rate, 36/225).
[C85] Md Masudur Rahman, Mythra Varun Balakuntala Srinivasa Mur, Mridul Agarwal, Upinder Kaur, Vishnunandan Lakshmi Venkatesh, Glebys Gonzalez, Natalia Sanchez Tamayo, Yexiang Xue, Richard Voyles, Vaneet Aggarwal, and Juan Wachs, "SARTRES: A Semi-Autonomous Robot TeleopeRation Environment for Surgery," in Proc. MICCAI 2020 Joint Workshop on Augmented Environments for Computer Assisted Interventions, Oct 2020.
[C84] Dheeraj Peddireddy, Xingyu Fu, Haobo Wang, Byung Gun Joung, Vaneet Aggarwal, John W Sutherland, and Martin Byung-Guk Jun, "Deep Learning Based Approach for Identifying Conventional Machining Processes from CAD Data," in Proc. NAMRC, Jun 2020.
[C83] Amrit Singh Bedi, Dheeraj Peddireddy, Vaneet Aggarwal, and Alec Koppel, "Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions," in Proc. L4DC, Jun 2020.
[C82] Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis, and Vaneet Aggarwal, "Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning," in Proc. ICASSP, May 2020.
[C81] Yifan Shen, Ke Liu, Ziting Guo, Wenli Zhang, Guanghui Zhang, Vaneet Aggarwal, and Mingyu Chen, "Freeway: an order-less user-space framework for non-real-time applications," in Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 225-228, May 2020.
[C80] Qinbo Bai, Mridul Agarwal, and Vaneet Aggarwal, "Escaping Saddle Points for Zeroth-order Nonconvex Optimization using Estimated Gradient Descent," in Proc. CISS, Mar 2020
[C79] Anis Elgabli, Jihong Park, Amrit Bedi, Mehdi Bennis, and Vaneet Aggarwal, "Communication Efficient Framework for Decentralized Machine Learning," in Proc. CISS, Mar 2020
[C78] Ashutosh Singh, Abubakr Alabbasi, and Vaneet Aggarwal, "A Reinforcement Learning Based Algorithm for Multi-hop Ride-sharing: Model-free Approach," in Proc. Neurips Workshop on Machine Learning for Autonomous Driving, Dec 2019.
[C77] Abubakr O. Alabbasi, Ali Elghariani, Anis Elgabli, and Vaneet Aggarwal, "On the Information Freshness and Tail Latency Trade-off in Mobile Networks," in Proc. Globecomm, Dec 2019.
[C76] Ramkumar Raghu, Pratheek Upadhyaya, Mahadesh Panju, Vaneet Aggarwal, and Vinod Sharma, "Deep Reinforcement Learning Based Power control for Wireless Multicast Systems," in Proc. Allerton, Oct 2019.
[C75] Yimeng Wang, Yongbo Li, Vaneet Aggarwal, and Tian Lan, "Deep Q-Learning for Chunk-based Caching in Data Processing Networks," in Proc. Allerton, Oct 2019.
[C74] Md Masudur Rahman, Natalia Sanchez-Tamayo, Glebys Gonzalez, Mridul Agarwal, Vaneet Aggarwal, Richard Voyles, Yexiang Xue, Juan Wachs, "Transferring Dexterous Surgical Skill Knowledge between Robots for Semi-autonomous Teleoperation," in Proc. IEEE International Conference on Robot and Human Interactive Communication (Ro-Man), Oct 2019.
[C73] Chinmayananda Arunachala, Vaneet Aggarwal, and B. Sundar Rajan, "Optimal Broadcast Rate of a Class of Two-Sender Unicast Index Coding Problem," in Proc. IEEE ITW, Aug 2019.
[C72] Nandan Sriranga, Chandra R. Murthy, and Vaneet Aggarwal, "A Method to Improve Consensus Averaging using Quantized ADMM," in Proc. IEEE ISIT, Jun 2019.
[C71] Anis Elgabli, Ali Elghariani, Vaneet Aggarwal, Mark R. Bell, and Mehdi Bennis, "A Proximal Jacobian ADMM Approach for Fast Massive MIMO Detection in Low-Latency Communications," in Proc. IEEE ICC, May 2019.
[C70] Mahadesh Panju, Ramkumar Raghu, Vaneet Agarwal, Vinod Sharma, and Rajesh Ramachandran, "Queuing Theoretic Models for Multicasting Under Fading," in Proc. IEEE WCNC, Apr 2019.
[C69] Anis Elgabli, Ali Elghariani, Vaneet Aggarwal, and Mark R. Bell, "QoE-Aware Resource Allocation for Small Cell," in Proc. Globecom, Dec 2018.
[C68] Arnob Ghosh, Randall Berry, and Vaneet Aggarwal, "Tiered Spectrum Measurement Markets for Licensed Secondary Spectrum", in Proc. International Conference on NETwork Games, COntrol and OPtimisation (NETGCOOP), Nov 2018.
[C67] Arnob Ghosh and Vaneet Aggarwal, “Menu-Based Pricing for Profitable Electric Vehicle Charging with Vehicle-to-Grid Service,” in Proc. IEEE SPCOM, Jul 2018
[C66] Abubakr Alabassi and Vaneet Aggarwal, “Stall-Quality Tradeoff for Cloud-based Video Streaming,” in Proc. IEEE SPCOM, Jul 2018
[C65] Anis Elgabli, Vaneet Aggarwal, and Ke Liu, “Low Complexity Algorithm for Multi-path Video Streaming,” in Proc. IEEE SPCOM, Jul 2018
[C64] Arnob Ghosh, Randall Berry, and Vaneet Aggarwal, "Spectrum Measurement Markets for Tiered Spectrum Access", in Proc. ICC, May 2018.
[C63] Abubakr O. Al-Abbasi and Vaneet Aggarwal, "EdgeCache: An Optimized Algorithm for CDN-based Over-the-top Video Streaming Services," in Proc. Infocom Workshop (International Workshop on Integrating Edge Computing, Caching, and Offloading in Next Generation Networks (IECCO)), Apr 2018.
[C62] Abubakr O. Al-Abbasi and Vaneet Aggarwal, "Mean Latency Optimization in Erasure-coded Distributed Storage Systems," in Proc. Infocom Workshop (International Workshop on Cloud Computing Systems, Networks, and Applications (CCSNA)), Apr 2018.
[C61] Ruijiu Mao, Vaneet Aggarwal, and Mung Chiang, "Stochastic Non-preemptive Co-flow Scheduling with Time-Indexed Relaxation," in Proc. Infocom Workshop (International Workshop on Big Data in Cloud Performance (DCPerf)), Apr 2018.
[C60] Anis Elgabli and Vaneet Aggarwal, "GroupCast: Preference-Aware Cooperative Video Streaming with Scalable Video Coding," in Proc. Infocom Workshop (International Workshop on Hot Topics in Pervasive Mobile and Online Social Networking (HotPOST'18)), Apr 2018 (Best paper award).
[C59] Morteza Ashraphijuo, Xiaodong Wang, and Vaneet Aggarwal, "An approximation of the CP-rank of a partially sampled tensor," in Proc. Allerton, Oct 2017.
[C58] Morteza Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "A characterization of sampling patterns for low-tucker-rank tensor completion problem," in Proc. IEEE ISIT, Jun 2017.
[C57] Morteza Ashraphijuo, Xiaodong Wang, and Vaneet Aggarwal, "A characterization of sampling patterns for low-rank multi-view data completion problem," in Proc. IEEE ISIT, Jun 2017.
[C56] Ke Liu, Vaneet Aggarwal, Ziyu Shao, and Mingyu Chen, "Joint Upload-Download TCP Acceleration Over Mobile Data Networks," in Proc. IEEE International Conference on Sensing, Communication and Networking (SECON), Jun 2017 (26.47% acceptance rate).
[C55] Vaneet Aggarwal, Mark R. Bell, Anis Elgabli, Xiaodong Wang, and Shan Zhong, "Joint Energy- Bandwidth Allocation for Multi-User Channels with Cooperating Hybrid Energy Nodes," in Proc. IEEE ICC (Green Communications Systems and Networks Symposium), May 2017.
[C54] Arnob Ghosh and Vaneet Aggarwal, "Electric Vehicle Charging with Menu-Based Pricing," in Proc. IEEE ICC (SAC Symposium Communications for the Smart Grid), May 2017.
[C53] Zhe Wang, Vaneet Aggarwal, Xiaodong Wang, and Muhammad Ismail, "Energy Scheduling for Optical Channels with Energy Harvesting Devices," in Proc. IEEE ICC (Green Communications Systems and Networks Symposium), May 2017.
[C52] Vaneet Aggarwal, Ajay A. Mahimkar, Hongyao Ma, Zemin Zhang, Shuchin Aeron, and Walter Willinger, "Inferring Smartphone Service Quality using Tensor Methods," in Proc. 12th International Conference on Network and Service Management Oct-Nov, 2016 (18% acceptance rate).
[C51] Vaneet Aggarwal and Shuchin Aeron, "A note on Information-theoretic Bounds on Matrix Completion under Union of Subspaces Model," in Proc. Allerton, Sept 2016.
[C50] Wenqi Wang, Shuchin Aeron, and Vaneet Aggarwal, "On deterministic conditions for subspace clustering under missing data," in Proc. IEEE ISIT, Jul 2016 (Extended version here).
[C49] Vaneet Aggarwal, Yih-Farn Robin Chen, Tian Lan, and Yu Xiang, "Sprout: A functional caching approach to minimize service latency in erasure-coded storage," in Proc. IEEE ICDCS, Jun 2016 (17.6% acceptance rate).
[C48] Xiao-Yang Liu, Shuchin Aeron, Vaneet Aggarwal, and Xiaodong Wang, "Low-tubal-rank Tensor Completion using Alternating Minimization," in Proc. SPIE Conference on Defense and Security, Apr 2016.
[C47] Xiao-Yang Liu, Shuchin Aeron, Vaneet Aggarwal, Xiaodong Wang, and Min-You Wu, "Tensor completion via adaptive sampling of tensor fibers: An application to efficient RF fingerprinting," in Proc. ICASSP, Mar 2016.
[C46] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "Energy Harvesting Communication Using Limited Battery With Efficiency," in Proc. Allerton, 2015.
[C45] Fernando Stefanello, Luciana S. Buriol, Vaneet Aggarwal, and Mauricio G. C. Resende, "A New Linear Model for Placement of Virtual Machines across Geo-Separated Data Centers" in Proc. Simpsio Brasileiro de Pesquisa Operacional (SBPO), Aug 2015.
[C44] Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Multi-Tenant Latency Optimization in Erasure-Coded Storage with Differentiated Services," in Proc. ICDCS, Jun-Jul. 2015 (13% acceptance rate).
[C43] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "Capacity of Two-Way Linear Deterministic Diamond Channel," in Proc. IEEE ISIT, Jun. 2015
[C42] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Energy-Subchannel Allocation for Energy Harvesting Nodes in Frequency-Selective Channels," in Proc. IEEE ISIT, Jun. 2015
[C41] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Energy-Bandwidth Allocation in Multiple Orthogonal Broadcast Channels with Energy Harvesting," in Proc. IEEE ISIT, Jun. 2015
[C40] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On the Symmetric K-user Linear Deterministic Interference Channels with Limited Feedback," in Proc. Allerton, Oct. 2014
[C39] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Optimal Energy-Bandwidth Allocation for Energy Harvesting Interference Networks," in Proc. IEEE ISIT, Jul. 2014
[C38] Vaneet Aggarwal, Jeff Pang, Emir Halepovic, Shobha Venkataraman, and He Yan, "Prometheus: Toward Quality-of-Experience Estimation for Mobile Apps from Passive Network Measurements," in Proc. ACM HotMobile, Feb. 2014.
[C37] Vaidyanathan Ramaswami, Kautubh Jain, Rittwik Jana, and Vaneet Aggarwal, "Modeling heavy-tails in traffic sources for network performance evaluation," in Proc. International Conference on Computational Intelligence, Cyber Security and Computational Models , Dec. 2013
[C36] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "Degrees of Freedom Region for MIMO Interference Channel with Limited Receiver Cooperation," in Proc. Allerton, Oct. 2013
[C35] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Renewable Energy Scheduling for Fading Channels with Maximum Power Constraint," in Proc. Allerton, Oct. 2013
[C34] Mehdi Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "Generalized Degrees of Freedom Region for MIMO Interference Channel with Perfect Feedback," in Proc. IEEE ISIT, July 2013
[C33] Chao Tian, Vaneet Aggarwal, and Vinay Vaishampayan, "Exact-Repair Regenerating Codes Via Layered Erasure Correction and Block Designs," in Proc. IEEE ISIT, July 2013
[C32] Vaneet Aggarwal, Melissa Duarte, Ashutosh Sabharwal, and N.K. Shankaranarayan, "Full- or Half-Duplex? A Capacity Analysis with Bounded Radio Resources," in Proc. IEEE ITW, Sept 2012.
[C31] Vaneet Aggarwal, "Writing on Insertion Paper," in Proc. IEEE ICC, June 2012.
[C30] Wei Pang, Peng Zhang, Tian Lan, and Vaneet Aggarwal, "Datacenter Net Profit Optimization with Deadline Dependent Pricing," in Proc. IEEE CISS, Mar 2012.
[C29] Khawla Al Najjar, Vaneet Aggarwal, Vinay Vaishampayan, and Xiaodong Wang, "Aligned Precoder Designs for Interference Channels based on Chordal Distance," in Proc. IEEE CISS, Mar 2012.
[C28] Vaneet Aggarwal, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan and Vinay Vaisham-payan, "Optimizing Cloud Resources for Delivering IPTV Services through Virtualization," in Proc. COMSNETS, Jan 2012.
[C27] Rajesh Panta, Rittwik Jana, Robert Hall, Josh Auzins, and Vaneet Aggarwal, "Scalable Geocast for Vehicular Networks," in Proc. IEEE Vehicular Networking Conference, Nov. 2011.
[C26] Vaneet Aggarwal, Rittwik Jana, Je rey Pang, Kadangode Ramakrishnan and N. K. Shankara-narayanan, "Characterizing Fairness for 3G Wireless Networks," in Proc. LANMAN, Oct. 2011.
[C25] Kanes Sutuntivorakoon, Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "Maximal k-Clique Scheduling: A Simple Algorithm to Bound Maximal Independent Graph Scheduling," in Proc. Allerton Conference, Sept 2011.
[C24] Vaneet Aggarwal, Xu Chen, Vijay Gopalakrishnan, Rittwik Jana, Kadangode Ramakrishnan and Vinay Vaishampayan, "Exploiting Virtualization for Delivering Cloud-based IPTV Services," in Proc. IEEE INFOCOM Workshop on Cloud Computing, Jan 2011.
[C23] Alireza Vahid, Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "On the Capacity of Multi-Hop Wireless Networks with Partial Network Knowledge," in Proc. Allerton Conference, Sept 2010.
[C22] Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "Normalized Sum-Capacity of Interference Networks with Partial Information," in Proc. IEEE ISIT, Jun 2010.
[C21] Satashu Goel, Vaneet Aggarwal, Aylin Yener and Robert Calderbank, "Modeling Location Uncertainty for Eavesdroppers: A Secrecy Graph Approach," in Proc. IEEE ISIT, Jun 2010.
[C20] Achaleshwar Sahai, Vaneet Aggarwal, Melda Yuksel and Ashutosh Sabharwal, "Sum Capacity of General Deterministic Interference Channel with Channel Output Feedback," in Proc. IEEE ISIT, Jun 2010.
[C19] Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "How (Information Theoretically) Optimal Are Distributed Decisions?," in Proc. IEEE CISS, Mar 2010.
[C18] Vaneet Aggarwal, Salman Avestimehr, Youjian Liu, and Ashutosh Sabharwal, "Feedback via Message Passing in Interference Channels," in Proc. IEEE ACSSC, Nov 2009, Pacific Grove, CA.
[C17] Vaneet Aggarwal, Lalitha Sankar, A. Robert Calderbank and H. Vincent Poor, "Ergodic Layered Erasure One-Sided Interference Channels," in Proc. IEEE ITW, Oct 2009.
[C16] Achaleshwar Sahai, Vaneet Aggarwal, Melda Yuksel and Ashutosh Sabharwal, "On Channel Output Feedback in Deterministic Interference Channels," in Proc. IEEE ITW, Oct 2009.
[C15] Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "Distributed Universally Optimal Strategies for Interference Channels with Partial Message Passing," in Proc. Allerton Conference, Sept.-Oct. 2009.
[C14] Vaneet Aggarwal, Lorne Applebaum, Amir Bennatan, A. Robert Calderbank, Stephen D. Howard and Stephen J. Searle, "Enhanced CDMA Communications using Compressed-Sensing Reconstruction Methods," in Proc. Allerton Conference, Sept.-Oct. 2009.
[C13] Jun Xiao, Vaneet Aggarwal, Ashutosh Sabharwal, and Youjian Liu, "Interference Networks with Local View: A Distributed Optimization Approach," in Proc. Allerton Conference, Sept.-Oct. 2009.
[C12] Vaneet Aggarwal, Lifeng Lai, A. Robert Calderbank and H. Vincent Poor, "Wiretap channel II with active eavesdroppers," in Proc. IEEE ISIT, Jun 2009.
[C11] Vaneet Aggarwal, Youjian Liu and Ashutosh Sabharwal, "Message Passing in Distributed Wireless Networks," in Proc. IEEE ISIT, Jun 2009.
[C10] Vaneet Aggarwal, Lalitha Sankar, A. Robert Calderbank and H. Vincent Poor, "Information Secrecy from Multiple Eavesdroppers in Orthogonal Relay Channels," in Proc. IEEE ISIT, Jun 2009.
[C9] Vaneet Aggarwal, A. Robert Calderbank, Gerald Gilbert and Yaakov S. Weinstein, "Engineering Fault Tolerance for Realistic Quantum Systems via the Full Error Dynamics of Quantum Codes," in Proc. IEEE ISIT, Jun 2009.
[C8] Gerald Gilbert, Yaakov S. Weinstein, Vaneet Aggarwal, and A. R. Calderbank, "Practical quantum fault tolerance," in Proc. SPIE 7342, Quantum Information and Computation VII, 734202, Apr 2019.
[C7] Vaneet Aggarwal, Lalitha Sankar, A. Robert Calderbank and H. Vincent Poor, "Secrecy capacity of a class of orthogonal relay eavesdropper channels," in Proc. IEEE ITA, Feb 2009.
[C6] Vaneet Aggarwal, Gajanana Krishna, Srikrishna Bhashyam and Ashutosh Sabharwal, "Two Models for Noisy Feedback in MIMO Channels," in Proc. IEEE ACSSC, Oct 2008, Pacific Grove, CA.
[C5] Vaneet Aggarwal and Ashutosh Sabharwal, "Diversity Order Gain with Noisy Feedback in Multiple Access Channels," in Proc. IEEE ISIT, Jul 2008, Toronto.
[C4] Vaneet Aggarwal and Ashutosh Sabharwal, "On Multiple Access Channels with Asymmetric Feedback," in Proc. IEEE ISIT, Jul 2008, Toronto.
[C3] Vaneet Aggarwal, Amir Bennatan and A. Robert Calderbank, "On Maximizing Coverage in Gaussian Relay Networks," in Proc. IEEE ITW, Jul 2007, Bergen.
[C2] Vaneet Aggarwal and A. Robert Calderbank, "Boolean Functions, Projection Operators, and Quantum Error Correcting Codes," in Proc. IEEE ISIT, Jun 2007, Nice.
[C1] Vaneet Aggarwal, Alexei Ashikhmin and A. Robert Calderbank, "A Grassmannian Packing Based on the Nordstrom-Robinson Code," in Proc. IEEE ITW, Oct 2006, Chengdu.
Conference Presentations without Proceedings:
[N29] Mohammad Ali Javidian, Vaneet Aggarwal, Fanglin Bao, and Zubin Jacob, "Quantum Entropic Causal Inference," Quantum Information and Measurement VI, Nov 2021.
[N28] Fanglin Bao, Hyunsoo Choi, Vaneet Aggarwal, Zubin Jacob, "Quantum acceleration in adaptive modal imaging of N stars," 2021 OSA Frontiers in Optics + Laser Science Conference, Oct-Nov 2021.
[N27] Kaushik Manchella, Abhishek K. Umrawal, and Vaneet Aggarwal, "FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Shared Passengers and Goods Delivery," ACM CSCS, Dec 2020.
[N26] Abubakr Alabbasi, Arnob Ghosh, and Vaneet Aggarwal, ``DeepPool: Distributed Model-free Algorithm for Ride-sharing using Deep Reinforcement Learning," ICAPS Featured Journal Paper, Oct 2020.
[N25] Kaushik Manchella, Abhishek K. Umrawal, and Vaneet Aggarwal, "FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Shared Passengers and Goods Delivery," ARMS Research Summit, Sept 2020.
[N24] Qinbo Bai, Ather Gattami, and Vaneet Aggarwal, ``Reinforcement Learning with Constraints," SPCOM, Bangalore, Jul 2020.
[N23] Ruijiu Mao and Vaneet Aggarwal, "Stochastic Scheduling on Related Machines with Precedence Constraints," SIAM Computational Science and Engineering Student Conference, Apr 2018.
[N22] Hamed Asadi, Jae Joong Lee, Vaneet Aggarwal, and Denny Yu, "Develop a computer-vision technique to predict force exertions using facial expressions and PPG signal," SIAM Computational Science and Engineering Student Conference, Apr 2018.
[N21] Vaneet Aggarwal and Arnob Ghosh, "Menu-based Pricing For Charging Of Electric Vehicles With Vehicle-to-grid Service," Informs Annual Meeting 2017.
[N20] Vaneet Aggarwal and Tian Lan, "Scheduling For Map-reduce Jobs," Informs Annual Meeting 2017.
[N19] Vaneet Aggarwal, Yang Zhang, Arnob Ghosh, and Tian Lan, "Tiered Cloud Storage Pricing Via Two-stage, Latency-aware Bidding," Informs Annual Meeting 2017.
[N18] Vaneet Aggarwal and Abubakr Alabassi , "Video Streaming In Distributed Erasure-coded Storage Systems," Informs Annual Meeting 2017.
[N17] Arnob Ghosh and Vaneet Aggarwal, "Control of Charging of Electric Vehicles through Menu-based pricing," Midwest Workshop on Control and Game Theory, 2017.
[N16] Yang Zhang, Arnob Ghosh, Vaneet Aggarwal, Tian Lan, Yu Xiang, and Robin Chen, "Tiered cloud storage pricing via two-stage, latency-aware bidding," Midwest Workshop on Control and Game Theory, 2017.
[N15] Abubakr Alabassi and Vaneet Aggarwal, "Video Streaming in Erasure Coded Distributed Storage Systems," Midwest Workshop on Control and Game Theory, 2017.
[N14] He Huang, Wenqi Wang, and Vaneet Aggarwal, "On Tensor Train Subspace Anomaly Detection via Oversampling," SIAM Computational Science and Engineering Student Conference, 2017.
[N13] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Tensor Train Subspace Embedding," SIAM Computational Science and Engineering Student Conference, 2017.
[N12] Abubakr Alabassi and Vaneet Aggarwal, "Online functional caching strategy for erasure-coded storage," SIAM Computational Science and Engineering Student Conference, 2017.
[N11] Tianqiong Luo, Vaneet Aggarwal, and Borja Peleato, "Coded caching with distributed storage," ITA 2017.
[N10] Morteza Ashraphijuo, Vaneet Aggarwal, and Xiaodong Wang, "On finite completability of low-rank tensors," ITA 2017.
[N9] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Joint energy and spectral resource scheduling for energy-harvesting transmitters," ITA 2015.
[N8] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, “Energy-harvesting wireless communications in fading channels”, WOCC 2014, NJ.
[N7] Zhe Wang, Vaneet Aggarwal, and Xiaodong Wang, "Energy scheduling for energy-harvesting transmitters in fading channels," ITA 2014.
[N6] Salman Avestimehr, Alireza Vahid, Vaneet Aggarwal, and Ashutosh Sabharwal, "Network capacity with local network views," ITA 2012.
[N5] Gerald Gilbert, Yaakov S. Weinstein, Vaneet Aggarwal and A. Robert Calderbank, "Analyses of Volume Thresholds in Quantum Fault Tolerance," in Proc. APS March Meeting 2010.
[N4] Vaneet Aggarwal, Salman Avestimehr, and Ashutosh Sabharwal, "Local view in networks: How good are distributed decisions?," ITA 2010.
[N3] Gerald Gilbert, Yaakov S. Weinstein, Vaneet Aggarwal and A. Robert Calderbank, "Operator Theoretic Quantum Fault Tolerance," in Proc. APS March Meeting 2009.
[N2] Vaneet Aggarwal, Lalitha Shankar, Robert Calderbank, and H. Vincent Poor, "Secrecy capacity of a class of orthogonal relay eavesdropper channels," ITA 2009.
[N1] Vaneet Aggarwal, A. Robert Calderbank, Gerald Gilbert, Mike Hamrick and Yaakov S. Weinstein, "A Universal Operator Theoretic Framework for Quantum Fault Tolerance", in Proc. APS March Meeting 2008.
Technical Reports:
[T16] Mohammad Pedramfar and Vaneet Aggarwal, "Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback," Mar 2023.
[T15] Bhargav Ganguly, Yulian Wu, Di Wang, and Vaneet Aggarwal, "Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning," Feb 2023.
[T14] Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini, and Marco Canini, "FilFL: Accelerating Federated Learning via Client Filtering," Feb 2023.
[T13] Yulian Wu, Chaowen Guan, Vaneet Aggarwal, and Di Wang, "Quantum Heavy-tailed Bandits," Jan 2023.
[T12] Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, and Vaneet Aggarwal, "Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming," Oct 2021.
[T11] Mohammad Ali Javidian, Vaneet Aggarwal, Fanglin Bao, and Zubin Jacob, "Quantum Entropic Causal Inference," Feb 2021
[T10] Arnob Ghosh and Vaneet Aggarwal, "Model Free Reinforcement Learning Algorithm for Stationary Mean field Equilibrium for Leader-Follower Mean Field Game," Dec 2020.
[T9] Mounssif Krouka, Anis Elgabli, Mohammed S. Elbamby, Cristina Perfecto, Mehdi Bennis, and Vaneet Aggarwal, "Cross Layer Optimization and Distributed Reinforcement Learning Approach for Tile-Based 360 Degree Wireless Video Streaming," Nov 2020.
[T8] Sathwik Chadaga, Mridul Agarwal, Vaneet Aggarwal, "Encoders and Decoders for Quantum Expander Codes Using Machine Learning," Sept 2019
[T7] Arnob Ghosh, Vaneet Aggarwal, Feng Qian, "A Robust Algorithm for Tile-based 360-degree Video Streaming with Uncertain FoV Estimation," Dec 2018.
[T6] Arnob Ghosh, Vaneet Aggarwal, Feng Qian, "A Rate Adaptation Algorithm for Tile-based 360-degree Video Streaming," Apr 2017.
[T5] Vaneet Aggarwal and Tian Lan, "Tail Index for a Distributed Storage System with Pareto File Size Distribution," arXiv, Jan 2017 (This was published as part of [J70], published in IEEE TNSM).
[T4] Vaneet Aggarwal, "Reliability of k-out-of-n Data Storage System with Deterministic Parallel and Serial Repair," arXiv, Nov 2016.
[T3] Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron, "Tensor Completion by Alternating Minimization under the Tensor Train (TT) Model," arXiv:1609.05587, Sept 2016 (Extended version for Tensor Ring Model Published in CVPR 2018, [C77] ).
[T2] Vaneet Aggarwal and Shankar Krishnan, "Achieving Approximate Soft Clustering in Data Streams," arXiv:1207.6199, Jul 2012
[T1] Vaneet Aggarwal, "Distributed Joint Source-Channel Coding for arbitrary memoryless correlated sources and Source coding for Markov correlated sources using LDPC codes," arXiv:0802.2666, Feb 2008