Xiaoqian Wang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 54

Top Topics

Temporal Structure

Unsupervised Dimensionality Reduction

Top Venues

Publications

Yipei Wang, Xiaoqian Wang
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective. AISTATS (2024)
Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, Jing Gao
SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation. CoRR (2024)
Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang
Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. CoRR (2024)
Xiaoze Liu, Feijie Wu, Tianyang Xu, Zhuo Chen, Yichi Zhang, Xiaoqian Wang, Jing Gao
Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. CoRR (2024)
Shenyu Lu, Junyi Chai, Xiaoqian Wang
Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness. KDD (2024)
Shenyu Lu, Yipei Wang, Xiaoqian Wang
Debiasing Attention Mechanism in Transformer without Demographics. ICLR (2024)
Tianchun Li, Chengxiang Wu, Pengyi Shi, Xiaoqian Wang
Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow. AAAI (2024)
Taeuk Jang, Xiaoqian Wang, Heng Huang
Adversarial Fairness Network. AAAI (2024)
Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang
Learning the irreversible progression trajectory of Alzheimer's disease. CoRR (2024)
Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang
Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. AISTATS (2024)
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. AAAI (2023)
Hong Qin, Jude Kong, Wandi Ding, Ramneek Ahluwalia, Christo El-Morr, Zeynep Engin, Jake Okechukwu Effoduh, Rebecca Hwa, Serena Jingchuan Guo, Laleh Seyyed-Kalantari, Sylvia Kiwuwa Muyingo, Candace Makeda Moore, Ravi Parikh, Reva Schwartz, Dongxiao Zhu, Xiaoqian Wang, Yiye Zhang
Towards Trustworthy Artificial Intelligence for Equitable Global Health. CoRR (2023)
Taeuk Jang, Xiaoqian Wang
Difficulty-Based Sampling for Debiased Contrastive Representation Learning. CVPR (2023)
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification. CoRR (2023)
Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Xuelong Li, Heng Huang
Iteratively Re-Weighted Method for Sparsity-Inducing Norms. IEEE Trans. Knowl. Data Eng. 35 (7) (2023)
Taeuk Jang, Pengyi Shi, Xiaoqian Wang
Group-Aware Threshold Adaptation for Fair Classification. AAAI (2022)
Yipei Wang, Xiaoqian Wang
"Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations. NeurIPS (2022)
Junyi Chai, Xiaoqian Wang
Fairness with Adaptive Weights. ICML (2022)
Junyi Chai, Xiaoqian Wang
Self-Supervised Fair Representation Learning without Demographics. NeurIPS (2022)
Junyi Chai, Taeuk Jang, Xiaoqian Wang
Fairness without Demographics through Knowledge Distillation. NeurIPS (2022)
Yipei Wang, Xiaoqian Wang
A Unified Study of Machine Learning Explanation Evaluation Metrics. CoRR (2022)
Xiaoqian Wang, Feiping Nie
Multi-Task Learning Via Sharing Inexact Low-Rank Subspace. ICASSP (2021)
Taeuk Jang, Feng Zheng, Xiaoqian Wang
Constructing a Fair Classifier with Generated Fair Data. AAAI (2021)
Taeuk Jang, Pengyi Shi, Xiaoqian Wang
Group-Aware Threshold Adaptation for Fair Classification. CoRR (2021)
Yipei Wang, Xiaoqian Wang
Self-Interpretable Model with Transformation Equivariant Interpretation. NeurIPS (2021)
Rui Wang, Xiaoqian Wang, David I. Inouye
Shapley Explanation Networks. ICLR (2021)
Yipei Wang, Xiaoqian Wang
Self-Interpretable Model with TransformationEquivariant Interpretation. CoRR (2021)
Rui Wang, Xiaoqian Wang, David I. Inouye
Shapley Explanation Networks. CoRR (2021)
Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi
On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. IJCAI (2021)
Haoyan Xu, Ziheng Duan, Yida Huang, Jie Feng, Anni Ren, Qianru Zhang, Pengyu Song, Xiaoqian Wang
Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting. CoRR (2020)
Yawen Huang, Feng Zheng, Danyang Wang, Junyu Jiang, Xiaoqian Wang, Ling Shao
Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks. IJCAI (2020)
Yida Huang, Haoyan Xu, Ziheng Duan, Anni Ren, Jie Feng, Qianru Zhang, Xiaoqian Wang
Modeling Complex Spatial Patterns with Temporal Features via Heterogenous Graph Embedding Networks. CoRR (2020)
Haoyan Xu, Ziheng Duan, Yunsheng Bai, Yida Huang, Anni Ren, Qianru Yu, Qianru Zhang, Yueyang Wang, Xiaoqian Wang, Yizhou Sun, Wei Wang
Multivariate Time Series Classification with Hierarchical Variational Graph Pooling. CoRR (2020)
Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong Li, Heng Huang
An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms. CoRR (2019)
Kamran Ghasedi, Xiaoqian Wang, Cheng Deng, Heng Huang
Balanced Self-Paced Learning for Generative Adversarial Clustering Network. CVPR (2019)
Xiaoqian Wang, Heng Huang
Approaching Machine Learning Fairness through Adversarial Network. CoRR (2019)
Kamran Ghasedi Dizaji, Xiaoqian Wang, Heng Huang
Semi-Supervised Generative Adversarial Network for Gene Expression Inference. KDD (2018)
Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, Heng Huang
Cognitive Assessment Prediction in Alzheimer's Disease by Multi-Layer Multi-Target Regression. Neuroinformatics 16 (3-4) (2018)
Xiaoqian Wang, Kamran Ghasedi Dizaji, Heng Huang
Conditional generative adversarial network for gene expression inference. Bioinform. 34 (17) (2018)
Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model. J. Comput. Biol. 25 (7) (2018)
Xiaoqian Wang, Weidong Cai, Dinggang Shen, Heng Huang
Temporal Correlation Structure Learning for MCI Conversion Prediction. MICCAI (3) (2018)
Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang
New Balanced Active Learning Model and Optimization Algorithm. IJCAI (2018)
Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
Quantitative trait loci identification for brain endophenotypes via new additive model with random networks. Bioinform. 34 (17) (2018)
Xiaoqian Wang, Hao Huang
Directional Label Rectification in Adaptive Graph. AAAI (2018)
Hong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang
Group Sparse Additive Machine. NIPS (2017)
Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
Longitudinal Genotype-Phenotype Association Study via Temporal Structure Auto-learning Predictive Model. RECOMB (2017)
Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang
Learning A Structured Optimal Bipartite Graph for Co-Clustering. NIPS (2017)
Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang
Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. IPMI (2017)
Feiping Nie, Xiaoqian Wang, Heng Huang
Multiclass Capped ℓp-Norm SVM for Robust Classifications. AAAI (2017)
Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang
Regularized Modal Regression with Applications in Cognitive Impairment Prediction. NIPS (2017)
Hongchang Gao, Xiaoqian Wang, Heng Huang
New Robust Clustering Model for Identifying Cancer Genome Landscapes. ICDM (2016)
Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang
The Constrained Laplacian Rank Algorithm for Graph-Based Clustering. AAAI (2016)
Xiaoqian Wang, Dinggang Shen, Heng Huang
Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease. MICCAI (1) (2016)
Xiaoqian Wang, Feiping Nie, Heng Huang
Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. KDD (2016)
Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang
Discriminative Unsupervised Dimensionality Reduction. IJCAI (2015)
Feiping Nie, Xiaoqian Wang, Heng Huang
Clustering and projected clustering with adaptive neighbors. KDD (2014)