Conference

[C47] SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation
Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, and Jing Gao
In the Nineteenth Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), main conference
Accepted to Appear

[C46] Fairness-Aware Online Positive-Unlabeled Learning
Hoin Jung, and Xiaoqian Wang
In the Nineteenth Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), industrial track
Accepted to Appear

[C45] A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks
Hoin Jung, Taeuk Jang, and Xiaoqian Wang
In the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), spotlight
Accepted to Appear

[C44] Great Minds Think Alike: The Universal Convergence Trend of Input Salience
Yipei Wang, Jeffrey Mark Siskind, and Xiaoqian Wang
In the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
Accepted to Appear

[C43] Neural Collapse Inspired Debiased Representation Learning for Min-Max Fairness
Shenyu Lu, Junyi Chai, and Xiaoqian Wang
In the Thirtieth SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024) [Code]

[C42] Benchmarking Deletion Metrics with the Principled Explanations
Yipei Wang, and Xiaoqian Wang
In the Forty-First International Conference on Machine Learning (ICML 2024) [Code]

[C41] FADES: Fair Disentanglement with Sensitive Relevance
Taeuk Jang, and Xiaoqian Wang
In the Forty-First IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024) [Code]

[C40] Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, and Heng Huang
In the Forty-First IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024) [Code]

[C39] Learning the Irreversible Progression Trajectory of Alzheimer's Disease
Yipei Wang, Bing He, Shannon Risacher, Andrew Saykin, Jingwen Yan, and Xiaoqian Wang
In the Twenty-First IEEE International Symposium on Biomedical Imaging (ISBI 2024) [Code]

[C38] Explainable Planar Multiband Antenna Designer with Wasserstein Generative Adversarial Network
Hoin Jung, Vinicius Cabral Do Nascimento, Hongyang Liu, Xiaoqian Wang, Cheng-Kok Koh, and Dan Jiao
In the IEEE International Symposium on Antennas and Propagation and ITNC-USNC-URSI Radio Science Meeting (AP-S/URSI 2024)

[C37] Unveiling Dynamics in Standard MRI Sequences through Motion Magnification Techniques
Zhaoying Pan, Vidhya Vijayakrishnan Nair, Qiuting Wen, Yunjie Tong, and Xiaoqian Wang
In Organization for Human Brain Mapping (OHBM 2024)
Accepted for a Poster Presentation

[C36] Debiasing Attention Mechanism in Transformer without Demographics
Shenyu Lu, Yipei Wang, and Xiaoqian Wang
In the Twelfth International Conference on Learning Representations (ICLR 2024) [Code]

[C35] Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning
Taeuk Jang, Hongchang Gao, Pengyi Shi, and Xiaoqian Wang
In the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024) [Code]

[C34] On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective
Yipei Wang, and Xiaoqian Wang
In the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024) [Code]

[C33] Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow
Tianchun Li, Chengxiang Wu, Pengyi Shi, and Xiaoqian Wang
In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024) [Code]

[C32] Adversarial Fairness Network
Taeuk Jang, Xiaoqian Wang, and Heng Huang
In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024) [Code]

[C31] Difficulty-based Sampling for Debiased Contrastive Representation Learning
Taeuk Jang, and Xiaoqian Wang
In Proceedings of the Fortieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023) [Code]

[C30] SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, and Jing Gao
In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)
Distinguished Paper Award.

[C29] Why Not Other Classes?: Towards Class-Contrastive Back-Propagation Explanations
Yipei Wang, and Xiaoqian Wang
In Proceedings of the Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022) [Code]

[C28] Self-Supervised Fair Representation Learning without Demographics
Junyi Chai, and Xiaoqian Wang
In Proceedings of the Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022) [Code]

[C27] Fairness without Demographics through Knowledge Distillation
Junyi Chai, Taeuk Jang, and Xiaoqian Wang
In Proceedings of the Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022) [Code]

[C26] Fairness with Adaptive Weights
Junyi Chai, and Xiaoqian Wang
In Proceedings of the 39th International Conference on Machine Learning (ICML 2022) [Code]

[C25] Group-Aware Threshold Adaptation for Fair Classification
Taeuk Jang, Pengyi Shi, and Xiaoqian Wang
In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022) [Code]
Acceptance rate: 15.0% (1349/9020)

[C24] Self-Interpretable Model with Transformation Equivariant Interpretation
Yipei Wang, and Xiaoqian Wang
In Proceedings of the Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS 2021) [Code]

[C23] Constructing a Fair Classifier with Generated Fair Data
Taeuk Jang, Feng Zheng, and Xiaoqian Wang
In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021) [Code]

[C22] Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, and David Inouye
In the Ninth International Conference on Learning Representations (ICLR 2021) [Code]

[C21] On the Convergence of Stochastic Compositional Gradient Descent Ascent Method
Hongchang Gao, Xiaoqian Wang, Lei Luo, and Xinghua Shi
In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI 2021)
Acceptance rate: 13.9% (587/4284)

[C20] Multi-Task Learning via Sharing Inexact Low-Rank Subspace
Xiaoqian Wang, and Feiping Nie
In the 46th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021)

[C19] Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks
Yawen Huang, Feng Zheng, Junyu Jiang, Danyang Wang, Xiaoqian Wang, and Ling Shao
In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI 2020)
Acceptance rate: 12.6% (592/4717)

[C18] Balanced Self-Paced Learning for Generative Adversarial Clustering Network
Kamran Ghasedi Dizaji, Xiaoqian Wang, Cheng Deng, and Heng Huang
In Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019)
Acceptance rate: 5.6% (288/5160), oral presentation

[C17] Semi-Supervised Generative Adversarial Network for Gene Expression Inference
Kamran Ghasedi Dizaji*, Xiaoqian Wang*, and Heng Huang (* co-first authors)
In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018)
Acceptance rate: 18.4% (181/983), research track

[C16] New Balanced Active Learning Model and Optimization Algorithm
Xiaoqian Wang, Yijun Huang, Ji Liu, and Heng Huang
In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018)

[C15] Directional Label Rectification in Adaptive Graph
Xiaoqian Wang, and Hao Huang
In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018)

[C14] Temporal Correlation Structure Learning for MCI Conversion Prediction
Xiaoqian Wang, Weidong Cai, Dinggang Shen, and Heng Huang
In Proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018)

[C13] Regularized Modal Regression with Applications in Cognitive Impairment Prediction
Xiaoqian Wang*, Hong Chen*, Weidong Cai, Dinggang Shen, and Heng Huang (* co-first authors)
In Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017)

[C12] Group Sparse Additive Machine
Hong Chen, Xiaoqian Wang, Cheng Deng, and Heng Huang
In Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017)

[C11] Learning A Structured Optimal Bipartite Graph for Co-Clustering
Feiping Nie, Xiaoqian Wang, Cheng Deng, and Heng Huang
In Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017)

[C10] Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-Learning Predictive Model
Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, and Heng Huang
In Proceedings of the 21st Annual International Conference on Research in Computational Molecular Biology (RECOMB 2017)

[C9] Predicting Interrelated Alzheimer’s Disease Outcomes via New Self-Learned Structured Low-Rank Model
Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, and Heng Huang
In Proceedings of the 25th Biennial International Conference on Information Processing in Medical Imaging (IPMI 2017)

[C8] Multiclass Capped \(p\)-Norm SVM for Robust Classifications
Feiping Nie, Xiaoqian Wang, and Heng Huang
In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017)

[C7] New Robust Clustering Model for Identifying Cancer Genome Landscapes
Hongchang Gao*, Xiaoqian Wang*, and Heng Huang (* co-first authors)
In Proceedings of the IEEE 16th International Conference on Data Mining (ICDM 2016)
Acceptance rate: 8.6% (78/904), regular paper

[C6] Structured Doubly Stochastic Matrix for Graph Based Clustering
Xiaoqian Wang, Feiping Nie, and Heng Huang
In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2016)
Acceptance rate: 6.3% (70/1115), oral presentation, research track

[C5] The Constrained Laplacian Rank Algorithm for Graph-Based Clustering
Feiping Nie, Xiaoqian Wang, Michael I. Jordan, and Heng Huang
In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)

[C4] Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer’s Disease
Xiaoqian Wang, Dinggang Shen, and Heng Huang
In Proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016)

[C3] Discriminative Unsupervised Dimensionality Reduction
Xiaoqian Wang, Yun Liu, Feiping Nie, and Heng Huang
In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015)

[C2] Clustering and Projected Clustering via Adaptive Neighbor Assignment
Feiping Nie, Xiaoqian Wang, and Heng Huang
In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014)
Acceptance rate: 14.6% (151/1036), research track

[C1] New Primal SVM Solver with Linear Computational Cost for Big Data Classifications
Feiping Nie, Yizhen Huang, Xiaoqian Wang, and Heng Huang
In Proceedings of the 31st International Conference on Machine Learning (ICML 2014)

Publication