Bei Jiang - RankMe

65 papers A* 17A 3Journal 42Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Bayesian Bootstrap Framework for Mutual Information Neural Estimation: Bridging Classical Mutual Information Learning and Bayesian Nonparametric Learning. Trans. Mach. Learn. Res. Forough Fazeli-Asl, Michael Minyi Zhang, Linglong Kong, Bei Jiang
2026	J	`jnl`	Fast online ℓ0 elastic net subspace clustering via a novel dictionary update strategy. Pattern Recognit. Wentao Qu, Lingchen Kong, Linglong Kong, Bei Jiang
2026	J	`jnl`	Resolving data imbalance in transfer learning: a simple random sampling approach. Stat. Comput. Andrei Afilipoaei, Venkata Shreya Kala, Jainish Mehta, Ce Zhang, Bei Jiang, Linglong Kong
2025	J	`jnl`	A Bayesian hierarchical model for orthogonal Tucker decomposition with oblivious tensor compression. Knowl. Inf. Syst. Matthew Pietrosanu, Bei Jiang, Linglong Kong
2025	J	`jnl`	A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation. CoRR Forough Fazeli-Asl, Michael Minyi Zhang, Bei Jiang, Linglong Kong
2025	A	`conf`	Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data. AISTATS Hongni Wang, Junxi Zhang, Na Li, Linglong Kong, Bei Jiang, Xiaodong Yan
2025	J	`jnl`	Budget-constrained Active Learning to Effectively De-censor Survival Data. CoRR Ali Parsaee, Bei Jiang, Zachary Friggstad, Russell Greiner
2025	A*	`conf`	CBMA: Improving Conformal Prediction through Bayesian Model Averaging. ICLR Pankaj Bhagwat, Linglong Kong, Bei Jiang
2025	J	`jnl`	Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks. CoRR Enze Shi, Linglong Kong, Bei Jiang
2025	A*	`conf`	Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference. ICML Ce Zhang, Yixin Han, Yafei Wang, Xiaodong Yan, Linglong Kong, Ting Li, Bei Jiang
2025	J	`jnl`	NMDAU-Net: A Novel Lightweight 3D Network for Precision Segmentation of Brain Gliomas in MRI. Int. J. Imaging Syst. Technol. Dongjie Li, Xiangyu Meng, Yu Liang, Bei Jiang, Jiaxin Ren
2025	J	`jnl`	Non-Asymptotic Analysis of Online Local Private Learning with SGD. CoRR Enze Shi, Jinhan Xie, Bei Jiang, Linglong Kong, Xuming He
2025	A	`conf`	Oblivious Johnson-Lindenstrauss embeddings for compressed Tucker decompositions. CIKM Matthew Pietrosanu, Bei Jiang, Linglong Kong
2025	J	`jnl`	Online federated learning framework for classification. CoRR Wenxing Guo, Jinhan Xie, Jianya Lu, Bei Jiang, Hongsheng Dai, Linglong Kong
2025	J	`jnl`	Predicting CRISPR Cas9 Off-Target Activities With a Two-Stage Deep Learning Framework. IEEE Trans. Comput. Biol. Bioinform. Tianshan Zhang, Bei Jiang, Guang Yang, Zhijie Bao, Jiajie Peng
2025	J	`jnl`	Spilt conformal prediction with missing response. Stat. Comput. Zhimiao Cao, Ce Zhang, Beibei Lian, Bei Jiang, Linglong Kong, Xiaodong Yan
2025	J	`jnl`	Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis. CoRR Enze Shi, Pankaj Bhagwat, Zhixian Yang, Linglong Kong, Bei Jiang
2024	A*	`conf`	A Bayesian Hierarchical Model for Orthogonal Tucker Decomposition with Oblivious Tensor Compression. ICDM Matthew Pietrosanu, Bei Jiang, Linglong Kong
2024	A*	`conf`	Analysis of Differentially Private Synthetic Data: A Measurement Error Approach. AAAI Yangdi Jiang, Yi Liu, Xiaodong Yan, Anne-Sophie Charest, Linglong Kong, Bei Jiang
2024	—	`conf`	Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations. NAACL-HLT Enze Shi, Lei Ding, Linglong Kong, Bei Jiang
2024	A*	`conf`	Distributional Reinforcement Learning with Regularized Wasserstein Loss. NeurIPS Ke Sun, Yingnan Zhao, Wulong Liu, Bei Jiang, Linglong Kong
2024	J	`jnl`	Evaluation of OpenAI o1: Opportunities and Challenges of AGI. CoRR Tianyang Zhong, Zhengliang Liu, Yi Pan, Yutong Zhang, Yifan Zhou, Shizhe Liang, Zihao Wu, Yanjun Lyu, Peng Shu, Xiaowei Yu, Chao Cao, Hanqi Jiang, Hanxu Chen, Yiwei Li, Junhao Chen, Huawen Hu, Yihen Liu, Huaqin Zhao, Shaochen Xu, Haixing Dai, Lin Zhao, Ruidong Zhang, Wei Zhao, Zhenyuan Yang, Jingyuan Chen, Peilong Wang, Wei Ruan, Hui Wang, Huan Zhao, Jing Zhang, Yiming Ren, Shihuan Qin, Tong Chen, Jiaxi Li, Arif Hassan Zidan, Afrar Jahin, Minheng Chen, Sichen Xia, Jason Holmes, Yan Zhuang, Jiaqi Wang, Bochen Xu, Weiran Xia, Jichao Yu, Kaibo Tang, Yaxuan Yang, Bolun Sun, Tao Yang, Guoyu Lu, Xianqiao Wang, Lilong Chai, He Li, Jin Lu, Lichao Sun, Xin Zhang, Bao Ge, Xintao Hu, Lian Zhang, Hua Zhou, Lu Zhang, Shu Zhang, Ninghao Liu, Bei Jiang, Linglong Kong, Zhen Xiang, Yudan Ren, Jun Liu, Xi Jiang, Yu Bao, Wei Zhang, Xiang Li, Gang Li, Wei Liu, Dinggang Shen, Andrea Sikora, Xiaoming Zhai, Dajiang Zhu, Tianming Liu
2024	J	`jnl`	Fast Fusion Clustering via Double Random Projection. Entropy Hongni Wang, Na Li, Yanqiu Zhou, Jingxin Yan, Bei Jiang, Linglong Kong, Xiaodong Yan
2024	J	`jnl`	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. Comput. Biol. Medicine Xin Zeng, Fan-Fang Meng, Xin Li, Kai-Yang Zhong, Bei Jiang, Yi Li
2024	J	`jnl`	Inference on High-dimensional Single-index Models with Streaming Data. J. Mach. Learn. Res. Dongxiao Han, Jinhan Xie, Jin Liu, Liuquan Sun, Jian Huang, Bei Jiang, Linglong Kong
2024	J	`jnl`	MMDTA: A Multimodal Deep Model for Drug-Target Affinity with a Hybrid Fusion Strategy. J. Chem. Inf. Model. Kai-Yang Zhong, Meng-Liang Wen, Fan-Fang Meng, Xin Li, Bei Jiang, Xin Zeng, Yi Li
2024	A*	`conf`	Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach. NeurIPS Lei Ding, Yang Hu, Nicole Denier, Enze Shi, Junxi Zhang, Qirui Hu, Karen D. Hughes, Linglong Kong, Bei Jiang
2024	A*	`conf`	Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility. AAAI Shanshan Zhao, Wenhai Cui, Bei Jiang, Linglong Kong, Xiaodong Yan
2024	A*	`conf`	Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data. ICML Yafei Wang, Bo Pan, Mei Li, Jianya Lu, Lingchen Kong, Bei Jiang, Linglong Kong
2024	J	`jnl`	Wavelet-based Bayesian approximate kernel method for high-dimensional data analysis. Comput. Stat. Wenxing Guo, Xueying Zhang, Bei Jiang, Linglong Kong, Yaozhong Hu
2023	A*	`conf`	Gaussian Differential Privacy on Riemannian Manifolds. NeurIPS Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang
2023	J	`jnl`	Gaussian Differential Privacy on Riemannian Manifolds. CoRR Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang
2023	A	`conf`	Optimal Smooth Approximation for Quantile Matrix Factorization. SDM Peng Liu, Yi Liu, Rui Zhu, Linglong Kong, Bei Jiang, Di Niu
2023	A*	`conf`	The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure. AAAI Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Haiyin Piao, Zhixiao Sun, Zhiwei Yang, Randy Goebel, Bei Jiang, Yi Chang
2023	J	`jnl`	Ultrahigh gain hot-electron tunneling transistor approaching the collection limit. Sci. China Inf. Sci. Jun Lin, Pengfei Luo, Xinpei Duan, Wujun Zhang, Chao Ma, Tong Bu, Wanhan Su, Bei Jiang, Guoli Li, Xuming Zou, Ting Yu, Lei Liao, Xingqiang Liu
2022	J	`jnl`	Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach. Entropy Matthew Pietrosanu, Linglong Kong, Yan Yuan, Rhonda C. Bell, Nicole Letourneau, Bei Jiang
2022	J	`jnl`	Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation. Frontiers Big Data Shenggang Hu, Jabir Alshehabi Al-Ani, Karen D. Hughes, Nicole Denier, Alla Konnikov, Lei Ding, Jinhan Xie, Yang Hu, Monideepa Tarafdar, Bei Jiang, Linglong Kong, Hongsheng Dai
2022	J	`jnl`	Class Interference of Deep Neural Networks. CoRR Dongcui Diao, Hengshuai Yao, Bei Jiang
2022	A*	`conf`	Conformalized Fairness via Quantile Regression. NeurIPS Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang
2022	J	`jnl`	Conformalized Fairness via Quantile Regression. CoRR Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang
2022	J	`jnl`	Distributional Reinforcement Learning via Sinkhorn Iterations. CoRR Ke Sun, Yingnan Zhao, Yi Liu, Bei Jiang, Linglong Kong
2022	J	`jnl`	How Does Value Distribution in Distributional Reinforcement Learning Help Optimization? CoRR Ke Sun, Bei Jiang, Linglong Kong
2022	A*	`conf`	Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. NeurIPS Yi Liu, Ke Sun, Bei Jiang, Linglong Kong
2022	J	`jnl`	Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. CoRR Yi Liu, Ke Sun, Linglong Kong, Bei Jiang
2022	J	`jnl`	Rapid Repurposing of Novel Combination Drugs for the Treatment of Heart Failure via a Computationally Guided Network Screening Approach. J. Chem. Inf. Model. Yunyuan Huang, Jiqun Wang, Jiaqi Liu, Donglei Shi, Xiaokang Li, Manjiong Wang, Taotao Lu, Bei Jiang, Conglong Xia, Houwen Lin, Yixiang Xu, Jian Li
2022	A*	`conf`	Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability. AAAI Yafei Wang, Bo Pan, Wei Tu, Peng Liu, Bei Jiang, Chao Gao, Wei Lu, Shangling Jui, Linglong Kong
2022	J	`jnl`	Sigmoidally Preconditioned Off-policy Learning: a new exploration method for reinforcement learning. CoRR Xing Chen, Dongcui Diao, Hechang Chen, Hengshuai Yao, Jielong Yang, Haiyin Piao, Zhixiao Sun, Bei Jiang, Yi Chang
2022	A*	`conf`	Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving. AAAI Lei Ding, Dengdeng Yu, Jinhan Xie, Wenxing Guo, Shenggang Hu, Meichen Liu, Linglong Kong, Hongsheng Dai, Yanchun Bao, Bei Jiang
2021	J	`jnl`	Advanced algorithms for penalized quantile and composite quantile regression. Comput. Stat. Matthew Pietrosanu, Jueyu Gao, Linglong Kong, Bei Jiang, Di Niu
2021	A*	`conf`	Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. NeurIPS Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
2021	J	`jnl`	Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization. CoRR Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
2021	A*	`conf`	Meta-HAR: Federated Representation Learning for Human Activity Recognition. WWW Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, Jianming Yang
2021	J	`jnl`	Meta-HAR: Federated Representation Learning for Human Activity Recognition. CoRR Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, Jianming Yang
2021	J	`jnl`	Similarity Embedding Networks for Robust Human Activity Recognition. CoRR Chenglin Li, Carrie Lu Tong, Di Niu, Bei Jiang, Xiao Zuo, Lei Cheng, Jian Xiong, Jianming Yang
2021	J	`jnl`	Similarity Embedding Networks for Robust Human Activity Recognition. ACM Trans. Knowl. Discov. Data Chenglin Li, Carrie Lu Tong, Di Niu, Bei Jiang, Xiao Zuo, Lei Cheng, Jian Xiong, Jianming Yang
2021	J	`jnl`	Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm. CoRR Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong
2021	J	`jnl`	Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving. CoRR Lei Ding, Dengdeng Yu, Jinhan Xie, Wenxing Guo, Shenggang Hu, Meichen Liu, Linglong Kong, Hongsheng Dai, Yanchun Bao, Bei Jiang
2020	J	`jnl`	Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions. Entropy Tong Su, Yafei Wang, Yi Liu, William G. Branton, Eugene Asahchop, Christopher Power, Bei Jiang, Linglong Kong, Niansheng Tang
2019	A*	`conf`	M-estimation in Low-Rank Matrix Factorization: A General Framework. ICDM Wei Tu, Peng Liu, Jingyu Zhao, Yi Liu, Linglong Kong, Guodong Li, Bei Jiang, Guangjian Tian, Hengshuai Yao
2019	J	`jnl`	Sparse wavelet estimation in quantile regression with multiple functional predictors. Comput. Stat. Data Anal. Dengdeng Yu, Li Zhang, Ivan Mizera, Bei Jiang, Linglong Kong
2018	J	`jnl`	Negative Log Likelihood Ratio Loss for Deep Neural Network Classification. CoRR Donglai Zhu, Hengshuai Yao, Bei Jiang, Peng Yu
2018	J	`jnl`	Personal Identification Based on Brain Networks of EEG Signals. Int. J. Appl. Math. Comput. Sci. Wanzeng Kong, Bei Jiang, Qiaonan Fan, Li Zhu, Xuehui Wei
2017	J	`jnl`	Assessment of driving fatigue based on intra/inter-region phase synchronization. Neurocomputing Wanzeng Kong, Zhanpeng Zhou, Bei Jiang, Fabio Babiloni, Gianluca Borghini
2017	—	`conf`	Task-Free Brainprint Recognition Based on Degree of Brain Networks. ICONIP (2) Wanzeng Kong, Qiaonan Fan, Luyun Wang, Bei Jiang, Yong Peng, Yanbin Zhang
2016	—	`conf`	A New EEG Signal Processing Method Based on Low-Rank and Sparse Decomposition. ICCSIP Wanzeng Kong, Yan Liu, Bei Jiang, Guojun Dai, Lin Xu