A New EEG Signal Processing Method Based on Low-Rank and Sparse Decomposition. - Wanzeng Kong; Yan Liu; Bei Jiang; Guojun Dai; Lin Xu (ICCSIP, 2016)

Task-Free Brainprint Recognition Based on Degree of Brain Networks. - Wanzeng Kong; Qiaonan Fan; Luyun Wang; Bei Jiang; Yong Peng 001; Yanbin Zhang (ICONIP (2), 2017)

Assessment of driving fatigue based on intra/inter-region phase synchronization. - Wanzeng Kong; Zhanpeng Zhou; Bei Jiang; Fabio Babiloni; Gianluca Borghini (Neurocomputing, 2017)

Personal Identification Based on Brain Networks of EEG Signals. - Wanzeng Kong; Bei Jiang; Qiaonan Fan; Li Zhu 005; Xuehui Wei (Int. J. Appl. Math. Comput. Sci., 2018)

Negative Log Likelihood Ratio Loss for Deep Neural Network Classification. - Donglai Zhu; Hengshuai Yao; Bei Jiang; Peng Yu (CoRR, 2018)

M-estimation in Low-Rank Matrix Factorization: A General Framework. - Wei Tu; Peng Liu 048; Jingyu Zhao 001; Yi Liu 062; Linglong Kong; Guodong Li; Bei Jiang; Guangjian Tian; Hengshuai Yao (ICDM, 2019)

Sparse wavelet estimation in quantile regression with multiple functional predictors. - Dengdeng Yu; Li Zhang 091; Ivan Mizera; Bei Jiang; Linglong Kong (Comput. Stat. Data Anal., 2019)

Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions. - Tong Su; Yafei Wang; Yi Liu 062; William G. Branton; Eugene Asahchop; Christopher Power; Bei Jiang; Linglong Kong; Niansheng Tang (Entropy, 2020)

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. - Ke Sun 013; Yafei Wang; Yi Liu 062; Yingnan Zhao; Bo Pan; Shangling Jui; Bei Jiang; Linglong Kong (NeurIPS, 2021)

Meta-HAR: Federated Representation Learning for Human Activity Recognition. - Chenglin Li; Di Niu; Bei Jiang; Xiao Zuo; Jianming Yang (WWW, 2021)

Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm. - Ke Sun 013; Yingnan Zhao; Yi Liu 062; Enze Shi; Yafei Wang; Aref Sadeghi; Xiaodong Yan; Bei Jiang; Linglong Kong (CoRR, 2021)

Advanced algorithms for penalized quantile and composite quantile regression. - Matthew Pietrosanu; Jueyu Gao; Linglong Kong; Bei Jiang; Di Niu (Comput. Stat., 2021)

Similarity Embedding Networks for Robust Human Activity Recognition. - Chenglin Li; Carrie Lu Tong; Di Niu; Bei Jiang; Xiao Zuo; Lei Cheng 005; Jian Xiong; Jianming Yang (ACM Trans. Knowl. Discov. Data, 2021)

Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving. - Lei Ding 013; Dengdeng Yu; Jinhan Xie; Wenxing Guo; Shenggang Hu; Meichen Liu; Linglong Kong; Hongsheng Dai; Yanchun Bao; Bei Jiang (AAAI, 2022)

Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability. - Yafei Wang; Bo Pan; Wei Tu; Peng Liu 048; Bei Jiang; Chao Gao; Wei Lu 023; Shangling Jui; Linglong Kong (AAAI, 2022)

Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. - Yi Liu 062; Ke Sun 013; Bei Jiang; Linglong Kong (NeurIPS, 2022)

Conformalized Fairness via Quantile Regression. - Meichen Liu; Lei Ding 013; Dengdeng Yu; Wulong Liu; Linglong Kong; Bei Jiang (NeurIPS, 2022)

Distributional Reinforcement Learning via Sinkhorn Iterations. - Ke Sun 013; Yingnan Zhao; Yi Liu 062; Bei Jiang; Linglong Kong (CoRR, 2022)

Sigmoidally Preconditioned Off-policy Learning: a new exploration method for reinforcement learning. - Xing Chen; Dongcui Diao; Hechang Chen; Hengshuai Yao; Jielong Yang; Haiyin Piao; Zhixiao Sun; Bei Jiang; Yi Chang 001 (CoRR, 2022)

How Does Value Distribution in Distributional Reinforcement Learning Help Optimization? - Ke Sun 013; Bei Jiang; Linglong Kong (CoRR, 2022)

Class Interference of Deep Neural Networks. - Dongcui Diao; Hengshuai Yao; Bei Jiang (CoRR, 2022)

Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach. - Matthew Pietrosanu; Linglong Kong; Yan Yuan; Rhonda C. Bell; Nicole Letourneau; Bei Jiang (Entropy, 2022)

Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation. - Shenggang Hu; Jabir Alshehabi Al-Ani; Karen D. Hughes; Nicole Denier; Alla Konnikov; Lei Ding 013; Jinhan Xie; Yang Hu; Monideepa Tarafdar; Bei Jiang; Linglong Kong; Hongsheng Dai (Frontiers Big Data, 2022)

Rapid Repurposing of Novel Combination Drugs for the Treatment of Heart Failure via a Computationally Guided Network Screening Approach. - Yunyuan Huang; Jiqun Wang; Jiaqi Liu; Donglei Shi; Xiaokang Li; Manjiong Wang; Taotao Lu; Bei Jiang; Conglong Xia; Houwen Lin; Yixiang Xu; Jian Li (J. Chem. Inf. Model., 2022)

The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure. - Xing Chen; Dongcui Diao; Hechang Chen; Hengshuai Yao; Haiyin Piao; Zhixiao Sun; Zhiwei Yang 005; Randy Goebel; Bei Jiang; Yi Chang 001 (AAAI, 2023)

Gaussian Differential Privacy on Riemannian Manifolds. - Yangdi Jiang; Xiaotian Chang; Yi Liu; Lei Ding 013; Linglong Kong; Bei Jiang (NeurIPS, 2023)

Optimal Smooth Approximation for Quantile Matrix Factorization. - Peng Liu 048; Yi Liu 062; Rui Zhu 007; Linglong Kong; Bei Jiang; Di Niu (SDM, 2023)

Ultrahigh gain hot-electron tunneling transistor approaching the collection limit. - Jun Lin; Pengfei Luo; Xinpei Duan; Wujun Zhang; Chao Ma; Tong Bu; Wanhan Su; Bei Jiang; Guoli Li; Xuming Zou; Ting Yu; Lei Liao; et al. (Sci. China Inf. Sci., 2023)

Analysis of Differentially Private Synthetic Data: A Measurement Error Approach. - Yangdi Jiang; Yi Liu; Xiaodong Yan; Anne-Sophie Charest; Linglong Kong; Bei Jiang (AAAI, 2024)

Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility. - Shanshan Zhao; Wenhai Cui; Bei Jiang; Linglong Kong; Xiaodong Yan (AAAI, 2024)

Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data. - Yafei Wang; Bo Pan; Mei Li; Jianya Lu; Lingchen Kong; Bei Jiang; Linglong Kong (ICML, 2024)

Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations. - Enze Shi; Lei Ding 013; Linglong Kong; Bei Jiang (NAACL-HLT, 2024)

Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach. - Lei Ding 013; Yang Hu; Nicole Denier; Enze Shi; Junxi Zhang; Qirui Hu; Karen D. Hughes; Linglong Kong; Bei Jiang (NeurIPS, 2024)

Distributional Reinforcement Learning with Regularized Wasserstein Loss. - Ke Sun 013; Yingnan Zhao; Wulong Liu; Bei Jiang; Linglong Kong (NeurIPS, 2024)

Evaluation of OpenAI o1: Opportunities and Challenges of AGI. - Tianyang Zhong; Zhengliang Liu; Yi Pan 001; Yutong Zhang; Yifan Zhou; Shizhe Liang; Zihao Wu 001; Yanjun Lyu; Peng Shu; Xiaowei Yu; Chao Cao; Hanqi Jiang; et al. (CoRR, 2024)

MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy. - Kai-Yang Zhong; Meng-Liang Wen; Fan-Fang Meng; Xin Li; Bei Jiang; Xin Zeng; Yi Li (J. Chem. Inf. Model., 2024)

GHGPR-PPIS: A graph convolutional network for identifying protein-protein interaction site using heat kernel with Generalized PageRank techniques and edge self-attention feature processing block. - Xin Zeng; Fan-Fang Meng; Xin Li; Kai-Yang Zhong; Bei Jiang; Yi Li (Comput. Biol. Medicine, 2024)

Fast Fusion Clustering via Double Random Projection. - Hongni Wang; Na Li; Yanqiu Zhou; Jingxin Yan; Bei Jiang; Linglong Kong; Xiaodong Yan (Entropy, 2024)

Wavelet-based Bayesian approximate kernel method for high-dimensional data analysis. - Wenxing Guo; Xueying Zhang; Bei Jiang; Linglong Kong; Yaozhong Hu (Comput. Stat., 2024)

Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data. - Hongni Wang; Junxi Zhang; Na Li; Linglong Kong; Bei Jiang; Xiaodong Yan (AISTATS, 2025)

CBMA: Improving Conformal Prediction through Bayesian Model Averaging. - Pankaj Bhagwat; Linglong Kong; Bei Jiang (ICLR, 2025)

NMDAU-Net: A Novel Lightweight 3D Network for Precision Segmentation of Brain Gliomas in MRI. - Dongjie Li; Xiangyu Meng; Yu Liang; Bei Jiang; Jiaxin Ren (Int. J. Imaging Syst. Technol., 2025)

A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation. - Forough Fazeli-Asl; Michael Minyi Zhang; Bei Jiang; Linglong Kong (CoRR, 2025)

Online federated learning framework for classification. - Wenxing Guo; Jinhan Xie; Jianya Lu; Bei Jiang; Hongsheng Dai; Linglong Kong (CoRR, 2025)

Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks. - Enze Shi; Linglong Kong; Bei Jiang (CoRR, 2025)

Non-Asymptotic Analysis of Online Local Private Learning with SGD. - Enze Shi; Jinhan Xie; Bei Jiang; Linglong Kong; Xuming He (CoRR, 2025)

A Bayesian hierarchical model for orthogonal Tucker decomposition with oblivious tensor compression. - Matthew Pietrosanu; Bei Jiang; Linglong Kong (Knowl. Inf. Syst., 2025)