Keywords 

Publication

Conference

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)
Accepted to Appear

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)
Accepted to Appear

Debiasing Attention Mechanism in Transformer without Demographics
Shenyu Lu, Yipei Wang, and Xiaoqian Wang
In the Twelfth International Conference on Learning Representations (ICLR 2024)
Accepted to Appear

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

Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow
Tianchun Li, Chengxiang Wu, Pengyi Shi, and Xiaoqian Wang
In the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024)
Accepted to Appear

Adversarial Fairness Network
Taeuk Jang, Xiaoqian Wang, and Heng Huang
In the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024)
Accepted to Appear

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

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.

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

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

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

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

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)

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]

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]

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

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)

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)

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)

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

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

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)

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

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)

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)

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)

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)

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)

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)

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)

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

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

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)

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)

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)

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

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)

Journal

Iteratively Re-Weighted Method for Sparsity-Inducing Norms
Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Xuelong Li, and Heng Huang
IEEE Transactions on Knowledge and Data Engineering 35, no. 7 (2023): 7045–7055

Determining the Role of Advection in Patterning by Bone Morphogenetic Proteins through Neural Network Model-based Acceleration of a 3D Finite Element Model of the Zebrafish Embryo
Linlin Li, Xu Wang, Junyi Chai, Xiaoqian Wang, Adrian Buganza Tepole, and David Umulis
Frontiers in Systems Biology (2022).

Identifying Imaging Markers for Predicting Cognitive Assessments Using Wasserstein Distances Based Matrix Regression
Jiexi Yan, Cheng Deng, Lei Luo, Xiaoqian Wang, Xiaohui Yao, Li Shen, and Heng Huang
Frontiers in Neuroscience 13, no. 668 (2019): 1–9

Conditional Generative Adversarial Network for Gene Expression Inference
Xiaoqian Wang*, Kamran Ghasedi Dizaji*, and Heng Huang (* co-first authors)
Bioinformatics 34, no. 17 (2018): i603–i611
Accepted by European Conference on Computational Biology (ECCB), acceptance rate: 17.1% (48/280)

Quantitative Trait Loci Identification for Brain Endophenotypes via New Additive Model with Random Networks
Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Bioinformatics 34, no. 17 (2018): i866–i874
Accepted by European Conference on Computational Biology (ECCB), acceptance rate: 17.1% (48/280)

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
Journal of Computational Biology 25, no. 7 (2018): 809–824. (Journal version of the RECOMB 2017 paper)

Cognitive Assessment Prediction in Alzheimer’s Disease by Multi-Layer Multi-Target Regression
Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, and Heng Huang
Neuroinformatics 16 (2018): 285–294

Patent

Label Rectification and Classification/Prediction for Multivariate Time Series Data
Hao Huang, Xiaoqian Wang
US Patent US10417083. (2019).

Thesis

New Nonlinear Machine Learning Algorithms with Applications to Biomedical Data Science
Xiaoqian Wang
Ph.D. Dissertation, University of Pittsburgh, 2019