Xiaoqian Wang

According to our database, Xiaoqian Wang authored at least 58 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks.

Hoin Jung, Taeuk Jang, Xiaoqian Wang

CoRR, 2024

Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs.

Xiaoze Liu, Feijie Wu, Tianyang Xu, Zhuo Chen, Yichi Zhang, Xiaoqian Wang, Jing Gao

CoRR, 2024

Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness.

Shenyu Lu, Junyi Chai, Xiaoqian Wang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Learning the Irreversible Progression Trajectory of Alzheimer's Disease.

Yipei Wang, Bing He, Shannon L. Risacher, Andrew J. Saykin, Jingwen Yan, Xiaoqian Wang

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Benchmarking Deletion Metrics with the Principled Explanations.

Yipei Wang, Xiaoqian Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Debiasing Attention Mechanism in Transformer without Demographics.

Shenyu Lu, Yipei Wang, Xiaoqian Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation.

Xiaoze Liu, Ting Sun, Tianyang Xu, Feijie Wu, Cunxiang Wang, Xiaoqian Wang, Jing Gao

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Fairness-Aware Online Positive-Unlabeled Learning.

Hoin Jung, Xiaoqian Wang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

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, Heng Huang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

FADES: Fair Disentanglement with Sensitive Relevance.

Taeuk Jang, Xiaoqian Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective.

Yipei Wang, Xiaoqian Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning.

Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow.

Tianchun Li, Chengxiang Wu, Pengyi Shi, Xiaoqian Wang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Adversarial Fairness Network.

Taeuk Jang, Xiaoqian Wang, Heng Huang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Iteratively Re-Weighted Method for Sparsity-Inducing Norms.

Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Xuelong Li, Heng Huang

IEEE Trans. Knowl. Data Eng., July, 2023

Towards Trustworthy Artificial Intelligence for Equitable Global Health.

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

CoRR, 2023

To be Robust and to be Fair: Aligning Fairness with Robustness.

Junyi Chai, Xiaoqian Wang

CoRR, 2023

Difficulty-Based Sampling for Debiased Contrastive Representation Learning.

Taeuk Jang, Xiaoqian Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.

Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Unified Study of Machine Learning Explanation Evaluation Metrics.

Yipei Wang, Xiaoqian Wang

CoRR, 2022

"Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations.

Yipei Wang, Xiaoqian Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Self-Supervised Fair Representation Learning without Demographics.

Junyi Chai, Xiaoqian Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fairness without Demographics through Knowledge Distillation.

Junyi Chai, Taeuk Jang, Xiaoqian Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fairness with Adaptive Weights.

Junyi Chai, Xiaoqian Wang

Proceedings of the International Conference on Machine Learning, 2022

Group-Aware Threshold Adaptation for Fair Classification.

Taeuk Jang, Pengyi Shi, Xiaoqian Wang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Self-Interpretable Model with TransformationEquivariant Interpretation.

Yipei Wang, Xiaoqian Wang

CoRR, 2021

Self-Interpretable Model with Transformation Equivariant Interpretation.

Yipei Wang, Xiaoqian Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Convergence of Stochastic Compositional Gradient Descent Ascent Method.

Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Shapley Explanation Networks.

Rui Wang, Xiaoqian Wang, David I. Inouye

Proceedings of the 9th International Conference on Learning Representations, 2021

Multi-Task Learning Via Sharing Inexact Low-Rank Subspace.

Xiaoqian Wang, Feiping Nie

Proceedings of the IEEE International Conference on Acoustics, 2021

Constructing a Fair Classifier with Generated Fair Data.

Taeuk Jang, Feng Zheng, Xiaoqian Wang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Multivariate Time Series Classification with Hierarchical Variational Graph Pooling.

Haoyan Xu, Ziheng Duan, Yunsheng Bai, Yida Huang, Anni Ren, Qianru Yu, Qianru Zhang, Yueyang Wang, Xiaoqian Wang, Yizhou Sun, Wei Wang

CoRR, 2020

Modeling Complex Spatial Patterns with Temporal Features via Heterogenous Graph Embedding Networks.

Yida Huang, Haoyan Xu, Ziheng Duan, Anni Ren, Jie Feng, Qianru Zhang, Xiaoqian Wang

CoRR, 2020

Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting.

Haoyan Xu, Ziheng Duan, Yida Huang, Jie Feng, Anni Ren, Qianru Zhang, Pengyu Song, Xiaoqian Wang

CoRR, 2020

Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks.

Yawen Huang, Feng Zheng, Danyang Wang, Junyu Jiang, Xiaoqian Wang, Ling Shao

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Approaching Machine Learning Fairness through Adversarial Network.

Xiaoqian Wang, Heng Huang

CoRR, 2019

An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms.

Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong Li, Heng Huang

CoRR, 2019

Balanced Self-Paced Learning for Generative Adversarial Clustering Network.

Kamran Ghasedi, Xiaoqian Wang, Cheng Deng, Heng Huang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Cognitive Assessment Prediction in Alzheimer's Disease by Multi-Layer Multi-Target Regression.

Xiaoqian Wang, Xiantong Zhen, Quanzheng Li, Dinggang Shen, Heng Huang

Neuroinformatics, 2018

Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model.

Xiaoqian Wang, Jingwen Yan, Xiaohui Yao, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang

J. Comput. Biol., 2018

Conditional generative adversarial network for gene expression inference.

Xiaoqian Wang, Kamran Ghasedi Dizaji, Heng Huang

Bioinform., 2018

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 Shen, Heng Huang

Bioinform., 2018

Temporal Correlation Structure Learning for MCI Conversion Prediction.

Xiaoqian Wang, Weidong Cai, Dinggang Shen, Heng Huang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Semi-Supervised Generative Adversarial Network for Gene Expression Inference.

Kamran Ghasedi Dizaji, Xiaoqian Wang, Heng Huang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

New Balanced Active Learning Model and Optimization Algorithm.

Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Directional Label Rectification in Adaptive Graph.

Xiaoqian Wang, Hao Huang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

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, Heng Huang

Proceedings of the Research in Computational Molecular Biology, 2017

Regularized Modal Regression with Applications in Cognitive Impairment Prediction.

Xiaoqian Wang, Hong Chen, Weidong Cai, Dinggang Shen, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning A Structured Optimal Bipartite Graph for Co-Clustering.

Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Group Sparse Additive Machine.

Hong Chen, Xiaoqian Wang, Cheng Deng, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 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, Heng Huang

Proceedings of the Information Processing in Medical Imaging, 2017

Multiclass Capped ℓp-Norm SVM for Robust Classifications.

Feiping Nie, Xiaoqian Wang, Heng Huang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease.

Xiaoqian Wang, Dinggang Shen, Heng Huang

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix.

Xiaoqian Wang, Feiping Nie, Heng Huang

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

New Robust Clustering Model for Identifying Cancer Genome Landscapes.

Hongchang Gao, Xiaoqian Wang, Heng Huang

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

The Constrained Laplacian Rank Algorithm for Graph-Based Clustering.

Feiping Nie, Xiaoqian Wang, Michael I. Jordan, Heng Huang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Discriminative Unsupervised Dimensionality Reduction.

Xiaoqian Wang, Yun Liu, Feiping Nie, Heng Huang

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Clustering and projected clustering with adaptive neighbors.

Feiping Nie, Xiaoqian Wang, Heng Huang

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014