Bei Jiang

According to our database, Bei Jiang authored at least 31 papers between 2016 and 2024.

Collaborative distances:

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

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, January, 2024

Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility.

Shanshan Zhao, Wenhai Cui, Bei Jiang, Linglong Kong, Xiaodong Yan

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

Analysis of Differentially Private Synthetic Data: A Measurement Error Approach.

Yangdi Jiang, Yi Liu, Xiaodong Yan, Anne-Sophie Charest, Linglong Kong, Bei Jiang

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

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, Xingqiang Liu

Sci. China Inf. Sci., June, 2023

Optimal Smooth Approximation for Quantile Matrix Factorization.

Peng Liu, Yi Liu, Rui Zhu, Linglong Kong, Bei Jiang, Di Niu

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Gaussian Differential Privacy on Riemannian Manifolds.

Yangdi Jiang, Xiaotian Chang, Yi Liu, Lei Ding, Linglong Kong, Bei Jiang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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, Randy Goebel, Bei Jiang, Yi Chang

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

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

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, Jinhan Xie, Yang Hu, Monideepa Tarafdar, Bei Jiang, Linglong Kong, Hongsheng Dai

Frontiers Big Data, 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

Class Interference of Deep Neural Networks.

Dongcui Diao, Hengshuai Yao, Bei Jiang

CoRR, 2022

How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?

Ke Sun, 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

CoRR, 2022

Distributional Reinforcement Learning via Sinkhorn Iterations.

Ke Sun, Yingnan Zhao, Yi Liu, Bei Jiang, Linglong Kong

CoRR, 2022

Conformalized Fairness via Quantile Regression.

Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang

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

Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy.

Yi Liu, Ke Sun, Bei Jiang, Linglong Kong

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

Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.

Yafei Wang, Bo Pan, Wei Tu, Peng Liu, Bei Jiang, Chao Gao, Wei Lu, Shangling Jui, Linglong Kong

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

Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving.

Lei Ding, Dengdeng Yu, Jinhan Xie, Wenxing Guo, Shenggang Hu, Meichen Liu, Linglong Kong, Hongsheng Dai, Yanchun Bao, Bei Jiang

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

2021

Similarity Embedding Networks for Robust Human Activity Recognition.

Chenglin Li, Carrie Lu Tong, Di Niu, Bei Jiang, Xiao Zuo, Lei Cheng, Jian Xiong, Jianming Yang

ACM Trans. Knowl. Discov. Data, 2021

Advanced algorithms for penalized quantile and composite quantile regression.

Matthew Pietrosanu, Jueyu Gao, Linglong Kong, Bei Jiang, Di Niu

Comput. Stat., 2021

Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm.

Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong

CoRR, 2021

Meta-HAR: Federated Representation Learning for Human Activity Recognition.

Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, Jianming Yang

Proceedings of the WWW '21: The Web Conference 2021, 2021

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization.

Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong

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

2020

Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.

Tong Su, Yafei Wang, Yi Liu, William G. Branton, Eugene Asahchop, Christopher Power, Bei Jiang, Linglong Kong, Niansheng Tang

Entropy, 2020

2019

Sparse wavelet estimation in quantile regression with multiple functional predictors.

Dengdeng Yu, Li Zhang, Ivan Mizera, Bei Jiang, Linglong Kong

Comput. Stat. Data Anal., 2019

M-estimation in Low-Rank Matrix Factorization: A General Framework.

Wei Tu, Peng Liu, Jingyu Zhao, Yi Liu, Linglong Kong, Guodong Li, Bei Jiang, Guangjian Tian, Hengshuai Yao

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

Negative Log Likelihood Ratio Loss for Deep Neural Network Classification.

Donglai Zhu, Hengshuai Yao, Bei Jiang, Peng Yu

CoRR, 2018

Personal Identification Based on Brain Networks of EEG Signals.

Wanzeng Kong, Bei Jiang, Qiaonan Fan, Li Zhu, Xuehui Wei

Int. J. Appl. Math. Comput. Sci., 2018

2017

Assessment of driving fatigue based on intra/inter-region phase synchronization.

Wanzeng Kong, Zhanpeng Zhou, Bei Jiang, Fabio Babiloni, Gianluca Borghini

Neurocomputing, 2017

Task-Free Brainprint Recognition Based on Degree of Brain Networks.

Wanzeng Kong, Qiaonan Fan, Luyun Wang, Bei Jiang, Yong Peng, Yanbin Zhang

Proceedings of the Neural Information Processing - 24th International Conference, 2017

2016

A New EEG Signal Processing Method Based on Low-Rank and Sparse Decomposition.

Wanzeng Kong, Yan Liu, Bei Jiang, Guojun Dai, Lin Xu

Proceedings of the Cognitive Systems and Signal Processing, 2016