Yingbin Liang - RankMe

382 papers A* 61A 11B 42C 2Misc 11Journal 226Unranked 28

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bridging Online and Offline RL: Contextual Bandit Learning for Multi-Turn Code Generation. CoRR Ziru Chen, Dongdong Chen, Ruinan Jin, Yingbin Liang, Yujia Xie, Huan Sun
2026	J	`jnl`	Constraint-Rectified Training for Efficient Chain-of-Thought. CoRR Qinhang Wu, Sen Lin, Ming Zhang, Yingbin Liang, Ness B. Shroff
2026	J	`jnl`	ConvexBench: Can LLMs Recognize Convex Functions? CoRR Yepeng Liu, Yu Huang, Yu-Xiang Wang, Yingbin Liang, Yuheng Bu
2026	J	`jnl`	HIPO: Instruction Hierarchy via Constrained Reinforcement Learning. CoRR Keru Chen, Jun Luo, Sen Lin, Yingbin Liang, Alvaro Velasquez, Nathaniel Bastian, Shaofeng Zou
2026	J	`jnl`	Learnable Chernoff Baselines for Inference-Time Alignment. CoRR Sunil Madhow, Yuchen Liang, Ness B. Shroff, Yingbin Liang, Yu-Xiang Wang
2026	J	`jnl`	On the Learning Dynamics of RLVR at the Edge of Competence. CoRR Yu Huang, Zixin Wen, Yuejie Chi, Yuting Wei, Aarti Singh, Yingbin Liang, Yuxin Chen
2026	J	`jnl`	Regret Bounds for Reinforcement Learning from Multi-Source Imperfect Preferences. CoRR Ming Shi, Yingbin Liang, Ness B. Shroff, Ananthram Swami
2026	J	`jnl`	Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation. CoRR Pei-Chi Pan, Yingbin Liang, Sen Lin
2026	J	`jnl`	Sharp Convergence Rates for Masked Diffusion Models. CoRR Yuchen Liang, Zhiheng Tan, Ness B. Shroff, Yingbin Liang
2026	J	`jnl`	Why Adam Can Beat SGD: Second-Moment Normalization Yields Sharper Tails. CoRR Ruinan Jin, Yingbin Liang, Shaofeng Zou
2025	A*	`conf`	A Theoretical Analysis of Self-Supervised Learning for Vision Transformers. ICLR Yu Huang, Zixin Wen, Yuejie Chi, Yingbin Liang
2025	J	`jnl`	Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models. CoRR Yuchen Liang, Renxiang Huang, Lifeng Lai, Ness B. Shroff, Yingbin Liang
2025	—	`conf`	AdaProx: A Novel Method for Bilevel Optimization under Pessimistic Framework. CPAL Ziwei Guan, Daouda Sow, Sen Lin, Yingbin Liang
2025	A*	`conf`	Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach. ICLR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining. CoRR Yingbin Liang, Lu Dai, Shuo Shi, Minghao Dai, Junliang Du, Haige Wang
2025	A*	`conf`	DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity. ICLR Zhen Qin, Zhuqing Liu, Songtao Lu, Yingbin Liang, Jia Liu
2025	J	`jnl`	Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees. CoRR Yuchen Liang, Yingbin Liang, Lifeng Lai, Ness B. Shroff
2025	A*	`conf`	Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining. ICLR Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans-Arno Jacobsen, Yingbin Liang
2025	J	`jnl`	Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining. CoRR Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans-Arno Jacobsen, Yingbin Liang
2025	A*	`conf`	How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias. ICML Ruiquan Huang, Yingbin Liang, Jing Yang
2025	J	`jnl`	How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias. CoRR Ruiquan Huang, Yingbin Liang, Jing Yang
2025	J	`jnl`	Large Language Models Achieve Gold Medal Performance at the International Olympiad on Astronomy & Astrophysics (IOAA). CoRR Lucas Carrit Delgado Pinheiro, Ziru Chen, Bruno Caixeta Piazza, Ness B. Shroff, Yingbin Liang, Yuan-Sen Ting, Huan Sun
2025	—	`conf`	Meta ControlNet: Enhancing Task Adaptation via Meta Learning. CPAL Junjie Yang, Jinze Zhao, Peihao Wang, Zhangyang Wang, Yingbin Liang
2025	J	`jnl`	Mixture-of-Transformers Learn Faster: A Theoretical Study on Classification Problems. CoRR Hongbo Li, Qinhang Wu, Sen Lin, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Monitoring State Transitions in Markovian Systems with Sampling Cost. CoRR Kumar Saurav, Ness B. Shroff, Yingbin Liang
2025	J	`jnl`	Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent. CoRR Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
2025	J	`jnl`	Object Detection for Medical Image Analysis: Insights from the RT-DETR Model. CoRR Weijie He, Yuwei Zhang, Ting Xu, Tai An, Yingbin Liang, Bo Zhang
2025	J	`jnl`	Provable In-Context Learning of Nonlinear Regression with Transformers. CoRR Hongbo Li, Lingjie Duan, Yingbin Liang
2025	J	`jnl`	Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis. J. Mach. Learn. Res. Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang
2025	J	`jnl`	Robust Offline Reinforcement Learning for Non-Markovian Decision Processes. IEEE Trans. Inf. Theory Ruiquan Huang, Yingbin Liang, Jing Yang
2025	A*	`conf`	Theory on Mixture-of-Experts in Continual Learning. ICLR Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness B. Shroff
2025	A*	`conf`	Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers. ICLR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Transformers Provably Learn Directed Acyclic Graphs via Kernel-Guided Mutual Information. CoRR Yuan Cheng, Yu Huang, Zhe Xiong, Yingbin Liang, Vincent Y. F. Tan
2025	A*	`conf`	Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow. ICLR Hongru Yang, Zhangyang Wang, Jason D. Lee, Yingbin Liang
2025	A*	`conf`	Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective. ICML Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness B. Shroff
2025	J	`jnl`	Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective. CoRR Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	A comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methods. CoRR Yihao Zhong, Yijing Wei, Yingbin Liang, Xiqing Liu, Rongwei Ji, Yiru Cang
2024	J	`jnl`	AI-EDGE: An NSF AI institute for future edge networks and distributed intelligence. AI Mag. Peizhong Ju, Chengzhang Li, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Advanced Multimodal Deep Learning Architecture for Image-Text Matching. CoRR Jinyin Wang, Haijing Zhang, Yihao Zhong, Yingbin Liang, Rongwei Ji, Yiru Cang
2024	—	`conf`	Algorithm Design for Online Meta-Learning with Task Boundary Detection. CPAL Daouda Sow, Sen Lin, Yingbin Liang, Junshan Zhang
2024	B	`conf`	Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? MobiHoc Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Can We Theoretically Quantify the Impacts of Local Updates on the Generalization Performance of Federated Learning? CoRR Peizhong Ju, Haibo Yang, Jia Liu, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Convolutional Neural Networks for Predictive Modeling of Lung Disease. CoRR Yingbin Liang, Xiqing Liu, Haohao Xia, Yiru Cang, Zitao Zheng, Yuanfang Yang
2024	—	`conf`	Designing Near-Optimal Partially Observable Reinforcement Learning. MILCOM Ming Shi, Yingbin Liang, Ness B. Shroff
2024	A*	`conf`	Doubly Robust Instance-Reweighted Adversarial Training. ICLR Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang
2024	J	`jnl`	Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches. CoRR Yinqiu Feng, Aoran Shen, Jiacheng Hu, Yingbin Liang, Shiru Wang, Junliang Du
2024	J	`jnl`	Faster algorithm and sharper analysis for constrained Markov decision process. Oper. Res. Lett. Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
2024	A*	`conf`	Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games. ICML Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	A*	`conf`	In-Context Learning with Representations: Contextual Generalization of Trained Transformers. NeurIPS Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
2024	J	`jnl`	In-Context Learning with Representations: Contextual Generalization of Trained Transformers. CoRR Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
2024	A*	`conf`	In-context Convergence of Transformers. ICML Yu Huang, Yuan Cheng, Yingbin Liang
2024	J	`jnl`	Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems. CoRR You Wu, Mengfang Sun, Hongye Zheng, Jinxin Hu, Yingbin Liang, Zhenghao Lin
2024	J	`jnl`	Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data. CoRR Aoran Shen, Minghao Dai, Jiacheng Hu, Yingbin Liang, Shiru Wang, Junliang Du
2024	J	`jnl`	Model Developmental Safety: A Safety-Centric Method and Applications in Vision-Language Models. CoRR Gang Li, Wendi Yu, Yao Yao, Wei Tong, Yingbin Liang, Qihang Lin, Tianbao Yang
2024	J	`jnl`	Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK. J. Mach. Learn. Res. Hongru Yang, Ziyu Jiang, Ruizhe Zhang, Yingbin Liang, Zhangyang Wang
2024	J	`jnl`	Non-asymptotic Convergence of Discrete-time Diffusion Models: New Approach and Improved Rate. CoRR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2024	A*	`conf`	Non-asymptotic Convergence of Training Transformers for Next-token Prediction. NeurIPS Ruiquan Huang, Yingbin Liang, Jing Yang
2024	J	`jnl`	Non-asymptotic Convergence of Training Transformers for Next-token Prediction. CoRR Ruiquan Huang, Yingbin Liang, Jing Yang
2024	A*	`conf`	On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback. ICLR Ziwei Guan, Yi Zhou, Yingbin Liang
2024	J	`jnl`	Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm. CoRR Guanming Huang, Aoran Shen, Yuxiang Hu, Junliang Du, Jiacheng Hu, Yingbin Liang
2024	A*	`conf`	Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes. ICLR Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang
2024	J	`jnl`	Provably Efficient Offline Reinforcement Learning With Trajectory-Wise Reward. IEEE Trans. Inf. Theory Tengyu Xu, Yue Wang, Shaofeng Zou, Yingbin Liang
2024	A*	`conf`	Provably Efficient UCB-type Algorithms For Learning Predictive State Representations. ICLR Ruiquan Huang, Yingbin Liang, Jing Yang
2024	J	`jnl`	Robust Offline Reinforcement Learning for Non-Markovian Decision Processes. CoRR Ruiquan Huang, Yingbin Liang, Jing Yang
2024	A	`conf`	Sample Complexity Characterization for Linear Contextual MDPs. AISTATS Junze Deng, Yuan Cheng, Shaofeng Zou, Yingbin Liang
2024	J	`jnl`	Sample Complexity Characterization for Linear Contextual MDPs. CoRR Junze Deng, Yuan Cheng, Shaofeng Zou, Yingbin Liang
2024	J	`jnl`	Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization. CoRR Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang
2024	J	`jnl`	Theory on Mixture-of-Experts in Continual Learning. CoRR Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers. CoRR Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2024	J	`jnl`	Toward General Function Approximation in Nonstationary Reinforcement Learning. IEEE J. Sel. Areas Inf. Theory Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	B	`conf`	Towards General Function Approximation in Nonstationary Reinforcement Learning. ISIT Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2024	A*	`conf`	Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis. NeurIPS Hongru Yang, Bhavya Kailkhura, Zhangyang Wang, Yingbin Liang
2024	J	`jnl`	Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis. CoRR Hongru Yang, Bhavya Kailkhura, Zhangyang Wang, Yingbin Liang
2024	J	`jnl`	Transformers Provably Learn Feature-Position Correlations in Masked Image Modeling. CoRR Yu Huang, Zixin Wen, Yuejie Chi, Yingbin Liang
2023	A*	`conf`	A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. ICML Ming Shi, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. CoRR Ming Shi, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Algorithm Design for Online Meta-Learning with Task Boundary Detection. CoRR Daouda Sow, Sen Lin, Yingbin Liang, Junshan Zhang
2023	J	`jnl`	Convergence and Generalization of Wide Neural Networks with Large Bias. CoRR Hongru Yang, Ziyu Jiang, Ruizhe Zhang, Zhangyang Wang, Yingbin Liang
2023	J	`jnl`	Doubly Robust Instance-Reweighted Adversarial Training. CoRR Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang
2023	J	`jnl`	Generalization Performance of Transfer Learning: Overparameterized and Underparameterized Regimes. CoRR Peizhong Ju, Sen Lin, Mark S. Squillante, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization. ICML Ziyi Chen, Yi Zhou, Yingbin Liang, Zhaosong Lu
2023	A*	`conf`	Global Convergence of Two-Timescale Actor-Critic for Solving Linear Quadratic Regulator. AAAI Xuyang Chen, Jingliang Duan, Yingbin Liang, Lin Zhao
2023	A*	`conf`	Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs. ICLR Yuan Cheng, Ruiquan Huang, Yingbin Liang, Jing Yang
2023	J	`jnl`	Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs. CoRR Yuan Cheng, Ruiquan Huang, Jing Yang, Yingbin Liang
2023	J	`jnl`	In-Context Convergence of Transformers. CoRR Yu Huang, Yuan Cheng, Yingbin Liang
2023	A	`conf`	Learning to Generalize Provably in Learning to Optimize. AISTATS Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang
2023	J	`jnl`	Learning to Generalize Provably in Learning to Optimize. CoRR Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang
2023	J	`jnl`	Lower Bounds and Accelerated Algorithms for Bilevel Optimization. J. Mach. Learn. Res. Kaiyi Ji, Yingbin Liang
2023	A*	`conf`	M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. ICLR Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang
2023	J	`jnl`	M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. CoRR Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang
2023	J	`jnl`	Meta ControlNet: Enhancing Task Adaptation via Meta Learning. CoRR Junjie Yang, Jinze Zhao, Peihao Wang, Zhangyang Wang, Yingbin Liang
2023	J	`jnl`	Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games. CoRR Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	A*	`conf`	Near-Optimal Adversarial Reinforcement Learning with Switching Costs. ICLR Ming Shi, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Near-Optimal Adversarial Reinforcement Learning with Switching Costs. CoRR Ming Shi, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Non-Convex Bilevel Optimization with Time-Varying Objective Functions. NeurIPS Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Non-Convex Bilevel Optimization with Time-Varying Objective Functions. CoRR Sen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Non-stationary Reinforcement Learning under General Function Approximation. ICML Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	J	`jnl`	Non-stationary Reinforcement Learning under General Function Approximation. CoRR Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
2023	J	`jnl`	Online Min-max Problems with Non-convexity and Non-stationarity. Trans. Mach. Learn. Res. Yu Huang, Yuan Cheng, Yingbin Liang, Longbo Huang
2023	A*	`conf`	Online Nonconvex Optimization with Limited Instantaneous Oracle Feedback. COLT Ziwei Guan, Yi Zhou, Yingbin Liang
2023	J	`jnl`	Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes. CoRR Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang
2023	A*	`conf`	Provably Efficient Algorithm for Nonstationary Low-Rank MDPs. NeurIPS Yuan Cheng, Jing Yang, Yingbin Liang
2023	J	`jnl`	Provably Efficient Algorithm for Nonstationary Low-Rank MDPs. CoRR Yuan Cheng, Jing Yang, Yingbin Liang
2023	J	`jnl`	Provably Efficient UCB-type Algorithms For Learning Predictive State Representations. CoRR Ruiquan Huang, Yingbin Liang, Jing Yang
2023	J	`jnl`	Pruning Before Training May Improve Generalization, Provably. CoRR Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang
2023	J	`jnl`	Rethinking PGD Attack: Is Sign Function Necessary? CoRR Junjie Yang, Tianlong Chen, Xuxi Chen, Zhangyang Wang, Yingbin Liang
2023	A*	`conf`	Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL. ICLR Ruiquan Huang, Jing Yang, Yingbin Liang
2023	A*	`conf`	Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning. ICLR Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning. CoRR Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Theoretical Hardness and Tractability of POMDPs in RL with Partial Hindsight State Information. CoRR Ming Shi, Yingbin Liang, Ness B. Shroff
2023	A*	`conf`	Theory on Forgetting and Generalization of Continual Learning. ICML Sen Lin, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2023	J	`jnl`	Theory on Forgetting and Generalization of Continual Learning. CoRR Sen Lin, Peizhong Ju, Yingbin Liang, Ness B. Shroff
2022	J	`jnl`	A Constrained Optimization Approach to Bilevel Optimization with Multiple Inner Minima. CoRR Daouda Sow, Kaiyi Ji, Ziwei Guan, Yingbin Liang
2022	A*	`conf`	A Unifying Framework of Off-Policy General Value Function Evaluation. NeurIPS Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2022	J	`jnl`	Data Sampling Affects the Complexity of Online SGD over Dependent Data. CoRR Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
2022	A	`conf`	Data sampling affects the complexity of online SGD over dependent data. UAI Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang
2022	A	`conf`	Deterministic policy gradient: Convergence analysis. UAI Huaqing Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang
2022	J	`jnl`	Global Convergence of Two-timescale Actor-Critic for Solving Linear Quadratic Regulator. CoRR Xuyang Chen, Jingliang Duan, Yingbin Liang, Lin Zhao
2022	—	`conf`	Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying
2022	A*	`conf`	Model-Based Offline Meta-Reinforcement Learning with Regularization. ICLR Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang
2022	J	`jnl`	Model-Based Offline Meta-Reinforcement Learning with Regularization. CoRR Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang
2022	A*	`conf`	On the Convergence Theory for Hessian-Free Bilevel Algorithms. NeurIPS Daouda Sow, Kaiyi Ji, Yingbin Liang
2022	A*	`conf`	PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method. ICLR Ziwei Guan, Tengyu Xu, Yingbin Liang
2022	A*	`conf`	Provable Benefit of Multitask Representation Learning in Reinforcement Learning. NeurIPS Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang
2022	J	`jnl`	Provable Benefit of Multitask Representation Learning in Reinforcement Learning. CoRR Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang
2022	A*	`conf`	Provable Generalization of Overparameterized Meta-learning Trained with SGD. NeurIPS Yu Huang, Yingbin Liang, Longbo Huang
2022	J	`jnl`	Provable Generalization of Overparameterized Meta-learning Trained with SGD. CoRR Yu Huang, Yingbin Liang, Longbo Huang
2022	J	`jnl`	Provably Efficient Offline Reinforcement Learning with Trajectory-Wise Reward. CoRR Tengyu Xu, Yingbin Liang
2022	J	`jnl`	Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL. CoRR Ruiquan Huang, Jing Yang, Yingbin Liang
2022	J	`jnl`	Self-Secure Capacity-Achieving Feedback Schemes of Gaussian Multiple-Access Wiretap Channels With Degraded Message Sets. IEEE Trans. Inf. Forensics Secur. Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai
2022	J	`jnl`	Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning. J. Mach. Learn. Res. Kaiyi Ji, Junjie Yang, Yingbin Liang
2022	J	`jnl`	Understanding generalization error of SGD in nonconvex optimization. Mach. Learn. Yi Zhou, Yingbin Liang, Huishuai Zhang
2022	A*	`conf`	Will Bilevel Optimizers Benefit from Loops. NeurIPS Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
2022	J	`jnl`	Will Bilevel Optimizers Benefit from Loops. CoRR Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying
2021	J	`jnl`	A Unified Off-Policy Evaluation Approach for General Value Function. CoRR Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	A*	`conf`	Bilevel Optimization: Convergence Analysis and Enhanced Design. ICML Kaiyi Ji, Junjie Yang, Yingbin Liang
2021	A*	`conf`	CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee. ICML Tengyu Xu, Yingbin Liang, Guanghui Lan
2021	A*	`conf`	Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. ICML Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	J	`jnl`	Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality. CoRR Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang
2021	J	`jnl`	ES-Based Jacobian Enables Faster Bilevel Optimization. CoRR Daouda Sow, Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process. CoRR Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
2021	A*	`conf`	Faster Non-asymptotic Convergence for Double Q-learning. NeurIPS Lin Zhao, Huaqing Xiong, Yingbin Liang
2021	A	`conf`	Finite-time theory for momentum Q-learning. UAI Bowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang
2021	J	`jnl`	Lower Bounds and Accelerated Algorithms for Bilevel Optimization. CoRR Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data. SIAM J. Math. Data Sci. Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney
2021	A*	`conf`	Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling. AAAI Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang
2021	J	`jnl`	PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method. CoRR Ziwei Guan, Tengyu Xu, Yingbin Liang
2021	A*	`conf`	Provably Faster Algorithms for Bilevel Optimization. NeurIPS Junjie Yang, Kaiyi Ji, Yingbin Liang
2021	J	`jnl`	Provably Faster Algorithms for Bilevel Optimization. CoRR Junjie Yang, Kaiyi Ji, Yingbin Liang
2021	A*	`conf`	Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry. ICLR Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
2021	J	`jnl`	Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry. CoRR Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang
2021	A	`conf`	Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms. AISTATS Tengyu Xu, Yingbin Liang
2021	J	`jnl`	Understanding Estimation and Generalization Error of Generative Adversarial Networks. IEEE Trans. Inf. Theory Kaiyi Ji, Yi Zhou, Yingbin Liang
2021	A	`conf`	When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence. AISTATS Ziwei Guan, Tengyu Xu, Yingbin Liang
2020	J	`jnl`	A Primal Approach to Constrained Policy Optimization: Global Optimality and Finite-Time Analysis. CoRR Tengyu Xu, Yingbin Liang, Guanghui Lan
2020	A*	`conf`	Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent. IJCAI Bowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang
2020	J	`jnl`	Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent. CoRR Bowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang
2020	A*	`conf`	Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. NeurIPS Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
2020	J	`jnl`	Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters. CoRR Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor
2020	J	`jnl`	Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang, H. Vincent Poor
2020	J	`jnl`	Enhancing physical layer security via channel feedback: a survey. EURASIP J. Wirel. Commun. Netw. Bin Dai, Chong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai (Shitz)
2020	J	`jnl`	Feedback Capacities of Gaussian Multiple-Access Wiretap Channels. CoRR Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai
2020	B	`conf`	Feedback Capacity of Gaussian Multiple-Access Wiretap Channel with Degraded Message Sets. ITW Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai Shitz
2020	A*	`conf`	Finite-Time Analysis for Double Q-learning. NeurIPS Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang
2020	J	`jnl`	Finite-Time Analysis for Double Q-learning. CoRR Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang
2020	J	`jnl`	Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross Entropy. IEEE Trans. Signal Process. Haoyu Fu, Yuejie Chi, Yingbin Liang
2020	A*	`conf`	History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms. ICML Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang
2020	J	`jnl`	Impact of Action-Dependent State and Channel Feedback on Gaussian Wiretap Channels. IEEE Trans. Inf. Theory Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai Shitz
2020	A*	`conf`	Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms. NeurIPS Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Improving Sample Complexity Bounds for Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Momentum Q-learning with Finite-Sample Convergence Guarantee. CoRR Bowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang
2020	J	`jnl`	Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms. CoRR Kaiyi Ji, Junjie Yang, Yingbin Liang
2020	J	`jnl`	Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms. CoRR Tengyu Xu, Zhe Wang, Yingbin Liang
2020	J	`jnl`	Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling. CoRR Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang
2020	C	`conf`	On the Capacity of Gaussian Multiple-Access Wiretap Channels with Feedback. ISITA Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai Shitz
2020	J	`jnl`	Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning. CoRR Kaiyi Ji, Junjie Yang, Yingbin Liang
2020	A*	`conf`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. IJCAI Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	J	`jnl`	Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. CoRR Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
2020	A*	`conf`	Reanalysis of Variance Reduced Temporal Difference Learning. ICLR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	J	`jnl`	Reanalysis of Variance Reduced Temporal Difference Learning. CoRR Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang
2020	—	`conf`	Robust Dynamic Spectrum Access in Adversarial Environments. ICC Ziwei Guan, Timothy Y. Hu, Joseph Palombo, Michael J. Liston, Donald J. Bucci, Yingbin Liang
2020	A*	`conf`	Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. AAAI Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
2020	J	`jnl`	Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. CoRR Ziwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang
2020	J	`jnl`	Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms. CoRR Tengyu Xu, Yingbin Liang
2020	J	`jnl`	Spectral Algorithms for Community Detection in Directed Networks. CoRR Zhe Wang, Yingbin Liang, Pengsheng Ji
2020	J	`jnl`	Spectral Algorithms for Community Detection in Directed Networks. J. Mach. Learn. Res. Zhe Wang, Yingbin Liang, Pengsheng Ji
2020	J	`jnl`	When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence. CoRR Ziwei Guan, Tengyu Xu, Yingbin Liang
2019	J	`jnl`	A note on inexact gradient and Hessian conditions for cubic regularized Newton's method. Oper. Res. Lett. Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2019	J	`jnl`	A simple convergence analysis of Bregman proximal gradient algorithm. Comput. Optim. Appl. Yi Zhou, Yingbin Liang, Lixin Shen
2019	A	`conf`	Cubic Regularization with Momentum for Nonconvex Optimization. UAI Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2019	—	`conf`	Distributed SGD Generalizes Well Under Asynchrony. Allerton Jayanth Regatti, Gaurav Tendolkar, Yi Zhou, Abhishek Gupta, Yingbin Liang
2019	J	`jnl`	Distributed SGD Generalizes Well Under Asynchrony. CoRR Jayanth Regatti, Gaurav Tendolkar, Yi Zhou, Abhishek Gupta, Yingbin Liang
2019	J	`jnl`	Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	J	`jnl`	Finite-Sample Analysis for SARSA and Q-Learning with Linear Function Approximation. CoRR Shaofeng Zou, Tengyu Xu, Yingbin Liang
2019	A*	`conf`	Finite-Sample Analysis for SARSA with Linear Function Approximation. NeurIPS Shaofeng Zou, Tengyu Xu, Yingbin Liang
2019	A*	`conf`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. ICML Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	J	`jnl`	Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization. CoRR Kaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang
2019	J	`jnl`	K-Medoids Clustering of Data Sequences With Composite Distributions. IEEE Trans. Signal Process. Tiexing Wang, Qunwei Li, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2019	B	`conf`	Local Geometry of Cross Entropy Loss in Learning One-Hidden-Layer Neural Networks. ISIT Haoyu Fu, Yuejie Chi, Yingbin Liang
2019	J	`jnl`	MIMO Gaussian State-Dependent Channels with a State-Cognitive Helper. Entropy Michael Dikshtein, Ruchen Duan, Yingbin Liang, Shlomo Shamai (Shitz)
2019	—	`conf`	SGD Converges to Global Minimum in Deep Learning via Star-convex Path. ICLR (Poster) Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh
2019	J	`jnl`	SGD Converges to Global Minimum in Deep Learning via Star-convex Path. CoRR Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh
2019	J	`jnl`	Secrecy Capacity of Colored Gaussian Noise Channels With Feedback. IEEE Trans. Inf. Theory Chong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai Shitz
2019	A*	`conf`	SpiderBoost and Momentum: Faster Variance Reduction Algorithms. NeurIPS Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
2019	J	`jnl`	State-Dependent Interference Channel With Correlated States. IEEE Trans. Inf. Theory Yunhao Sun, Ruchen Duan, Yingbin Liang, Shlomo Shamai Shitz
2019	A	`conf`	Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. AISTATS Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2019	B	`conf`	The Dirty Paper Wiretap Feedback Channel with or without Action on the State. ISIT Bin Dai, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai Shitz
2019	A*	`conf`	Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples. NeurIPS Tengyu Xu, Shaofeng Zou, Yingbin Liang
2019	J	`jnl`	Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples. CoRR Tengyu Xu, Shaofeng Zou, Yingbin Liang
2018	B	`conf`	A Coding Scheme for Colored Gaussian Wiretap Channels with Feedback. ISIT Chong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2018	J	`jnl`	A Note on Inexact Condition for Cubic Regularized Newton's Method. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	Misc	`conf`	Clustering under composite generative models. CISS Tiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2018	A*	`conf`	Convergence of Cubic Regularization for Nonconvex Optimization under KL Property. NeurIPS Yi Zhou, Zhe Wang, Yingbin Liang
2018	J	`jnl`	Convergence of Cubic Regularization for Nonconvex Optimization under KL Property. CoRR Yi Zhou, Zhe Wang, Yingbin Liang
2018	J	`jnl`	Convergence of SGD in Learning ReLU Models with Separable Data. CoRR Tengyu Xu, Yi Zhou, Kaiyi Ji, Yingbin Liang
2018	—	`conf`	Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties. ICLR (Poster) Yi Zhou, Yingbin Liang
2018	J	`jnl`	Cubic Regularization with Momentum for Nonconvex Optimization. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	J	`jnl`	Data-Driven Nonparametric Existence and Association Problems. IEEE Trans. Signal Process. Yixian Liu, Yingbin Liang, Shuguang Cui
2018	Misc	`conf`	Data-Driven Nonparametric Hypothesis Testing. ICASSP Yixian Liu, Yingbin Liang, Shuguang Cui
2018	J	`jnl`	Degraded Broadcast Channel With Secrecy Outside a Bounded Range. IEEE Trans. Inf. Theory Shaofeng Zou, Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai Shitz
2018	J	`jnl`	Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters. J. Mach. Learn. Res. Yi Zhou, Yingbin Liang, Yaoliang Yu, Wei Dai, Eric P. Xing
2018	J	`jnl`	Estimation of KL Divergence: Optimal Minimax Rate. IEEE Trans. Inf. Theory Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
2018	Misc	`conf`	Exponentially Consistent K-Means Clustering Algorithm Based on Kolmogrov-Smirnov Test. ICASSP Tiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2018	J	`jnl`	Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization. CoRR Yi Zhou, Yingbin Liang, Huishuai Zhang
2018	J	`jnl`	K-medoids Clustering of Data Sequences with Composite Distributions. CoRR Tiexing Wang, Qunwei Li, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2018	J	`jnl`	Local Geometry of One-Hidden-Layer Neural Networks for Logistic Regression. CoRR Haoyu Fu, Yuejie Chi, Yingbin Liang
2018	J	`jnl`	MR-GAN: Manifold Regularized Generative Adversarial Networks. CoRR Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Yi Zhou, Yingbin Liang, Pramod K. Varshney
2018	J	`jnl`	Median-Truncated Nonconvex Approach for Phase Retrieval With Outliers. IEEE Trans. Inf. Theory Huishuai Zhang, Yuejie Chi, Yingbin Liang
2018	A*	`conf`	Minimax Estimation of Neural Net Distance. NeurIPS Kaiyi Ji, Yingbin Liang
2018	J	`jnl`	Minimax Estimation of Neural Net Distance. CoRR Kaiyi Ji, Yingbin Liang
2018	J	`jnl`	Nonparametric Composite Hypothesis Testing in an Asymptotic Regime. IEEE J. Sel. Top. Signal Process. Qunwei Li, Tiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2018	J	`jnl`	Parallel Gaussian Channels Corrupted by Independent States With a State-Cognitive Helper. CoRR Michael Dikshtein, Ruchen Duan, Yingbin Liang, Shlomo Shamai
2018	J	`jnl`	Sample Complexity of Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization. CoRR Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
2018	J	`jnl`	Secrecy Capacity of Colored Gaussian Noise Channels with Feedback. CoRR Chong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2018	J	`jnl`	SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization. CoRR Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh
2018	J	`jnl`	State-Dependent Gaussian Multiple Access Channels: New Outer Bounds and Capacity Results. IEEE Trans. Inf. Theory Wei Yang, Yingbin Liang, Shlomo Shamai Shitz, H. Vincent Poor
2018	J	`jnl`	State-Dependent Interference Channel with Correlated States. CoRR Yunhao Sun, Ruchen Duan, Yingbin Liang, Shlomo Shamai
2017	J	`jnl`	A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms. J. Mach. Learn. Res. Huishuai Zhang, Yingbin Liang, Yuejie Chi
2017	J	`jnl`	Characterization of Gradient Dominance and Regularity Conditions for Neural Networks. CoRR Yi Zhou, Yingbin Liang
2017	A*	`conf`	Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization. ICML Qunwei Li, Yi Zhou, Yingbin Liang, Pramod K. Varshney
2017	J	`jnl`	Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization. CoRR Qunwei Li, Yi Zhou, Yingbin Liang, Pramod K. Varshney
2017	J	`jnl`	Critical Points of Neural Networks: Analytical Forms and Landscape Properties. CoRR Yi Zhou, Yingbin Liang
2017	Misc	`conf`	Demixing sparse signals via convex optimization. ICASSP Yi Zhou, Yingbin Liang
2017	—	`conf`	Gaussian fading channel with secrecy outside a bounded range. CNS Shaofeng Zou, Yingbin Liang, Shlomo Shamai
2017	J	`jnl`	Multi-Key Generation Over a Cellular Model With a Helper. IEEE Trans. Inf. Theory Huishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai Shitz
2017	J	`jnl`	Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent. CoRR Yuanxin Li, Yuejie Chi, Huishuai Zhang, Yingbin Liang
2017	J	`jnl`	Nonparametric Composite Hypothesis Testing in an Asymptotic Regime. CoRR Qunwei Li, Tiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney
2017	J	`jnl`	Nonparametric Detection of Anomalous Data Streams. IEEE Trans. Signal Process. Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi
2017	J	`jnl`	Nonparametric Detection of Geometric Structures Over Networks. IEEE Trans. Signal Process. Shaofeng Zou, Yingbin Liang, H. Vincent Poor
2017	J	`jnl`	On the Sum-Rate Capacity of Poisson MISO Multiple Access Channels. IEEE Trans. Inf. Theory Ain Ul Aisha, Lifeng Lai, Yingbin Liang, Shlomo Shamai Shitz
2017	B	`conf`	Outer bounds for Gaussian multiple access channels with state known at one encoder. ISIT Wei Yang, Yingbin Liang, Shlomo Shamai Shitz, H. Vincent Poor
2017	B	`conf`	Secrecy capacity of the first-order autoregressive moving average Gaussian channel with feedback. ISIT Chong Li, Yingbin Liang
2017	J	`jnl`	State-Dependent Gaussian Multiple Access Channels: New Outer Bounds and Capacity Results. CoRR Wei Yang, Yingbin Liang, Shlomo Shamai, H. Vincent Poor
2017	B	`conf`	State-dependent Z-interference channel with correlated states. ISIT Yunhao Sun, Yingbin Liang, Ruchen Duan, Shlomo Shamai Shitz
2017	J	`jnl`	Sum-Rate Capacity of Poisson MIMO Multiple-Access Channels. IEEE Trans. Commun. Ain Ul Aisha, Lifeng Lai, Yingbin Liang, Shlomo Shamai Shitz
2016	J	`jnl`	Capacity Characterization for State-Dependent Gaussian Channel With a Helper. IEEE Trans. Inf. Theory Yunhao Sun, Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai Shitz
2016	J	`jnl`	Degraded Broadcast Channel with Secrecy Outside a Bounded Range. CoRR Shaofeng Zou, Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai
2016	J	`jnl`	Estimation of KL Divergence: Optimal Minimax Rate. CoRR Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
2016	B	`conf`	Estimation of KL divergence between large-alphabet distributions. ISIT Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
2016	—	`conf`	Geometrical properties and accelerated gradient solvers of non-convex phase retrieval. Allerton Yi Zhou, Huishuai Zhang, Yingbin Liang
2016	B	`conf`	Helper-assisted state cancelation for multiple access channels. ISIT Yunhao Sun, Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai
2016	B	`conf`	K-user degraded broadcast channel with secrecy outside a bounded range. ITW Shaofeng Zou, Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai
2016	J	`jnl`	Nonparametric Decentralized Detection and Sparse Sensor Selection Via Weighted Kernel. IEEE Trans. Signal Process. Weiguang Wang, Yingbin Liang, Eric P. Xing, Lixin Shen
2016	Misc	`conf`	Nonparametric composite outlier detection. ACSSC Weiguang Wang, Yingbin Liang, H. Vincent Poor
2016	Misc	`conf`	Nonparametric detection of an anomalous disk over a two-dimensional lattice network. ICASSP Shaofeng Zou, Yingbin Liang, H. Vincent Poor
2016	—	`conf`	On Compressive orthonormal Sensing. Allerton Yi Zhou, Huishuai Zhang, Yingbin Liang
2016	A	`conf`	On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System. AISTATS Yi Zhou, Yaoliang Yu, Wei Dai, Yingbin Liang, Eric P. Xing
2016	B	`conf`	On the sum-rate capacity of non-symmetric Poisson multiple access channel. ISIT Ain Ul Aisha, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2016	Misc	`conf`	On the sum-rate capacity of poisson MISO multiple access channels. ICCS Ain Ul Aisha, Lifeng Lai, Yingbin Liang, Shlomo Shamai Shitz
2016	A*	`conf`	Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow. ICML Huishuai Zhang, Yuejie Chi, Yingbin Liang
2016	—	`conf`	Reshaped Wirtinger Flow for Solving Quadratic System of Equations. NIPS Huishuai Zhang, Yingbin Liang
2016	J	`jnl`	Reshaped Wirtinger Flow for Solving Quadratic Systems of Equations. CoRR Huishuai Zhang, Yingbin Liang
2016	J	`jnl`	State-Dependent Gaussian Interference Channels: Can State Be Fully Canceled? IEEE Trans. Inf. Theory Ruchen Duan, Yingbin Liang, Shlomo Shamai Shitz
2016	Misc	`conf`	Universal outlying sequence detection for continuous observations. ICASSP Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
2015	J	`jnl`	An Information Theoretic Approach to Secret Sharing. IEEE Trans. Inf. Theory Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2015	—	`conf`	Analysis of Robust PCA via Local Incoherence. NIPS Huishuai Zhang, Yi Zhou, Yingbin Liang
2015	J	`jnl`	Bounds and Capacity Theorems for Cognitive Interference Channels With State. IEEE Trans. Inf. Theory Ruchen Duan, Yingbin Liang
2015	J	`jnl`	Broadcast Networks With Layered Decoding and Layered Secrecy: Theory and Applications. Proc. IEEE Shaofeng Zou, Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai
2015	J	`jnl`	Collective Support Recovery for Multi-Design Multi-Response Linear Regression. IEEE Trans. Inf. Theory Weiguang Wang, Yingbin Liang, Eric P. Xing
2015	B	`conf`	Degraded broadcast channel: Secrecy outside of a bounded range. ITW Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2015	J	`jnl`	On the Capacity Bounds for Poisson Interference Channels. IEEE Trans. Inf. Theory Lifeng Lai, Yingbin Liang, Shlomo Shamai (Shitz)
2015	J	`jnl`	Optimal Power Allocation for Poisson Channels With Time-Varying Background Light. IEEE Trans. Commun. Ain Ul Aisha, Lifeng Lai, Yingbin Liang
2015	B	`conf`	Rate splitting and sharing for degraded broadcast channel with secrecy outside a bounded range. ISIT Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2015	B	`conf`	Secret key capacity: Talk or keep silent? ISIT Huishuai Zhang, Yingbin Liang, Lifeng Lai
2015	J	`jnl`	Secure Communications via Physical-Layer and Information-Theoretic Techniques [Scanning the Issue]. Proc. IEEE Phillip A. Regalia, Ashish Khisti, Yingbin Liang, Stefano Tomasin
2015	—	`conf`	Sequential parallel LASSO models for eQTL analysis. BCB Anhong He, Benika Hall, Jia Wen, Yingbin Liang, Xinghua Shi
2015	J	`jnl`	State-Dependent Parallel Gaussian Networks With a Common State-Cognitive Helper. IEEE Trans. Inf. Theory Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai Shitz
2015	B	`conf`	State-dependent Gaussian Z-interference channel: Capacity results. ISIT Ruchen Duan, Yingbin Liang, Shlomo Shamai
2015	B	`conf`	Two-key generation for a cellular model with a helper. ISIT Huishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2015	J	`jnl`	Universal Outlying sequence detection For Continuous Observations. CoRR Yuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli
2014	J	`jnl`	A Broadcast Approach for Fading Wiretap Channels. IEEE Trans. Inf. Theory Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai
2014	—	`conf`	A kernel-based nonparametric test for anomaly detection over line networks. MLSP Shaofeng Zou, Yingbin Liang, H. Vincent Poor
2014	J	`jnl`	An Information Theoretic Approach to Secret Sharing. CoRR Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2014	C	`conf`	Dirty interference cancelation for multiple access channels. ISITA Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai
2014	B	`conf`	Dirty interference cancellation for Gaussian broadcast channels. ITW Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai
2014	Misc	`conf`	Helper-assisted asymmetric two key generation. ACSSC Huishuai Zhang, Yingbin Liang, Lifeng Lai
2014	—	`conf`	Kernel-based nonparametric anomaly detection. SPAWC Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi
2014	B	`conf`	Key capacity region for a cellular source model. ITW Huishuai Zhang, Yingbin Liang, Lifeng Lai
2014	B	`conf`	Layered secure broadcasting over MIMO channels and application in secret sharing. ISIT Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2014	J	`jnl`	Nonparametric Detection of Anomalous Data via Kernel Mean Embedding. CoRR Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi
2014	Misc	`conf`	On fading poisson channels with varying noise levels. CISS Ain Ul Aisha, Lifeng Lai, Yingbin Liang
2014	J	`jnl`	Parallel Gaussian Networks with a Common State-Cognitive Helper. CoRR Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai
2014	B	`conf`	Secret key-private key generation over three terminals: Capacity region. ISIT Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang
2014	—	`conf`	Sparse sensor selection for nonparametric decentralized detection via L1 regularization. MLSP Weiguang Wang, Yingbin Liang, Eric P. Xing, Lixin Shen
2014	B	`conf`	State-dependent parallel Gaussian channels with a common helper in high power regime. ISIT Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai
2014	J	`jnl`	The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation. CoRR Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang
2014	J	`jnl`	The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation. IEEE Trans. Inf. Theory Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang
2014	—	`conf`	Unsupervised nonparametric anomaly detection: A kernel method. Allerton Shaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi
2013	A	`conf`	Block Regularized Lasso for Multivariate Multi-Response Linear Regression. AISTATS Weiguang Wang, Yingbin Liang, Eric P. Xing
2013	—	`conf`	Layered decoding and secrecy over degraded broadcast channels. SPAWC Shaofeng Zou, Yingbin Liang, Lifeng Lai, Shlomo Shamai
2013	B	`conf`	Multiple access channel with state uncertainty at transmitters. ISIT Shaofeng Zou, Yingbin Liang, Shlomo Shamai
2013	B	`conf`	On the capacity region of Gaussian interference channels with state. ISIT Ruchen Duan, Yingbin Liang, Shlomo Shamai
2013	J	`jnl`	Sharp Threshold for Multivariate Multi-Response Linear Regression via Block Regularized Lasso. CoRR Weiguang Wang, Yingbin Liang, Eric P. Xing
2013	B	`conf`	State-dependent Gaussian Z-channel with mismatched side-information and interference. ITW Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai (Shitz)
2012	J	`jnl`	A Unified Framework for Key Agreement Over Wireless Fading Channels. IEEE Trans. Inf. Forensics Secur. Lifeng Lai, Yingbin Liang, H. Vincent Poor
2012	J	`jnl`	Bounds and Capacity Theorems for Cognitive Interference Channels with State CoRR Ruchen Duan, Yingbin Liang
2012	B	`conf`	Broadcasting over fading wiretap channels. ISIT Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai (Shitz)
2012	J	`jnl`	Cooperative Key Generation in Wireless Networks. IEEE J. Sel. Areas Commun. Lifeng Lai, Yingbin Liang, Wenliang Du
2012	B	`conf`	Gaussian cognitive interference channels with state. ISIT Ruchen Duan, Yingbin Liang
2012	B	`conf`	Nonparametric decentralized detection based on weighted count kernel. ISIT Jiayao Hu, Yingbin Liang, Eric P. Xing
2012	J	`jnl`	Special issue on physical-layer security. J. Commun. Networks Matthieu R. Bloch, Mérouane Debbah, Yingbin Liang, Yasutada Oohama, Andrew Thangaraj
2011	—	`conf`	Capacity bounds for a class of cognitive interference channels with state. Allerton Ruchen Duan, Yingbin Liang
2011	J	`jnl`	Distributed Cognitive Radio Network Management via Algorithms in Probabilistic Graphical Models. IEEE J. Sel. Areas Commun. Yingbin Liang, Lifeng Lai, John Halloran
2011	J	`jnl`	Fading Cognitive Multiple-Access Channels With Confidential Messages. IEEE Trans. Inf. Theory Ruoheng Liu, Yingbin Liang, H. Vincent Poor
2011	J	`jnl`	Fading Multiple Access Relay Channels: Achievable Rates and Opportunistic Scheduling. IEEE Trans. Inf. Theory Lalitha Sankar, Yingbin Liang, Narayan B. Mandayam, Harold Vincent Poor
2011	—	`conf`	Nonparametric decision making based on tree-structured information aggregation. Allerton Jiayao Hu, Yingbin Liang, Eric P. Xing
2011	J	`jnl`	On the Equivalence of Two Achievable Regions for the Broadcast Channel. IEEE Trans. Inf. Theory Yingbin Liang, Gerhard Kramer, H. Vincent Poor
2011	—	`conf`	PHY-based cooperative key generation in wireless networks. Allerton Lifeng Lai, Yingbin Liang, Wenliang Du
2011	J	`jnl`	Secrecy Throughput of MANETs Under Passive and Active Attacks. IEEE Trans. Inf. Theory Yingbin Liang, H. Vincent Poor, Lei Ying
2011	B	`conf`	Secret sharing via noisy broadcast channels. ISIT Lifeng Lai, Yingbin Liang, Wenliang Du, Shlomo Shamai
2011	J	`jnl`	Secure Communications Over Wireless Broadcast Networks: Stability and Utility Maximization. IEEE Trans. Inf. Forensics Secur. Yingbin Liang, H. Vincent Poor, Lei Ying
2010	—	`conf`	Key agreement over wireless fading channels with an active attacker. Allerton Lifeng Lai, Yingbin Liang, H. Vincent Poor
2010	J	`jnl`	Multiple-Input Multiple-Output Gaussian Broadcast Channels With Common and Confidential Messages. IEEE Trans. Inf. Theory Hung D. Ly, Tie Liu, Yingbin Liang
2010	B	`conf`	On the capacity region of the Poisson interference channels. ISIT Lifeng Lai, Yingbin Liang, Shlomo Shamai
2010	J	`jnl`	Optimality of beamforming for MIMO multiple access channels via virtual representation. IEEE Trans. Signal Process. Hong Wan, Rong-Rong Chen, Yingbin Liang
2009	J	`jnl`	Capacity of Cognitive Interference Channels With and Without Secrecy. IEEE Trans. Inf. Theory Yingbin Liang, Anelia Somekh-Baruch, H. Vincent Poor, Shlomo Shamai, Sergio Verdú
2009	J	`jnl`	Compound Wiretap Channels. EURASIP J. Wirel. Commun. Netw. Yingbin Liang, Gerhard Kramer, H. Vincent Poor, Shlomo Shamai (Shitz)
2009	—	`conf`	Distributed algorithm for collaborative detection in cognitive radio networks. Allerton Yingbin Liang, Lifeng Lai, John Halloran
2009	J	`jnl`	Fading Cognitive Multiple-Access Channels With Confidential Messages CoRR Ruoheng Liu, Yingbin Liang, H. Vincent Poor
2009	—	`conf`	Fading cognitive multiple-access channels with confidential messages. Allerton Ruoheng Liu, Yingbin Liang, H. Vincent Poor
2009	J	`jnl`	Information Theoretic Security. Found. Trends Commun. Inf. Theory Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2009	J	`jnl`	Multiple-Input Multiple-Output Gaussian Broadcast Channels with Common and Confidential Messages CoRR Hung D. Ly, Tie Liu, Yingbin Liang
2009	J	`jnl`	On the Compound MIMO Broadcast Channels with Confidential Messages CoRR Mari Kobayashi, Yingbin Liang, Shlomo Shamai, Mérouane Debbah
2009	B	`conf`	On the compound MIMO broadcast channels with confidential messages. ISIT Mari Kobayashi, Yingbin Liang, Shlomo Shamai, Mérouane Debbah
2009	J	`jnl`	Opportunistic Communications in Fading Multiaccess Relay Channels CoRR Lalitha Sankar, Yingbin Liang, Narayan B. Mandayam, H. Vincent Poor
2009	J	`jnl`	Outer Bounds on the Admissible Source Region for Broadcast Channels with Dependent Sources CoRR Gerhard Kramer, Yingbin Liang, Shlomo Shamai
2009	J	`jnl`	Physical layer security in broadcast networks. Secur. Commun. Networks Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2009	B	`conf`	Secrecy throughput of MANETs with malicious nodes. ISIT Yingbin Liang, H. Vincent Poor, Lei Ying
2008	B	`conf`	Capacity outer bounds for broadcast channels. ITW Yingbin Liang, Gerhard Kramer, Shlomo Shamai
2008	—	`conf`	Equivalence of two inner bounds on the capacity region of the broadcast channel. Allerton Yingbin Liang, Gerhard Kramer, H. Vincent Poor
2008	J	`jnl`	Multiple-Access Channels With Confidential Messages. IEEE Trans. Inf. Theory Yingbin Liang, H. Vincent Poor
2008	B	`conf`	Nested codes for secure transmission. PIMRC Ruoheng Liu, H. Vincent Poor, Predrag Spasojevic, Yingbin Liang
2008	B	`conf`	Optimality of beamforming in MIMO multi-access channels via virtual representation. ISIT Hong Wan, Rong-Rong Chen, Yingbin Liang
2008	B	`conf`	Recent results on compound wire-tap channels. PIMRC Yingbin Liang, Gerhard Kramer, H. Vincent Poor, Shlomo Shamai
2008	J	`jnl`	Secure Communication Over Fading Channels. IEEE Trans. Inf. Theory Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2008	—	`conf`	Session MA3a: Relaying and cooperation I. ACSCC Yingbin Liang
2007	J	`jnl`	Cognitive Interference Channels with Confidential Messages CoRR Yingbin Liang, Anelia Somekh-Baruch, H. Vincent Poor, Shlomo Shamai, Sergio Verdú
2007	J	`jnl`	Cooperative Relay Broadcast Channels. IEEE Trans. Inf. Theory Yingbin Liang, Venugopal V. Veeravalli
2007	J	`jnl`	Information-Theoretic Security in Wireless Networks CoRR Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2007	J	`jnl`	Opportunistic Communications in an Orthogonal Multiaccess Relay Channel CoRR Lalitha Sankar, Yingbin Liang, H. Vincent Poor, Narayan B. Mandayam
2007	B	`conf`	Opportunistic Communications in an Orthogonal Multiaccess Relay Channel. ISIT Lalitha Sankar, Yingbin Liang, H. Vincent Poor, Narayan B. Mandayam
2007	J	`jnl`	Rate Regions for Relay Broadcast Channels. IEEE Trans. Inf. Theory Yingbin Liang, Gerhard Kramer
2007	J	`jnl`	Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution CoRR Yingbin Liang, Venugopal V. Veeravalli, H. Vincent Poor
2007	J	`jnl`	Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution. IEEE Trans. Inf. Theory Yingbin Liang, Venugopal V. Veeravalli, H. Vincent Poor
2007	J	`jnl`	Secrecy Capacity Region of Binary and Gaussian Multiple Access Channels CoRR Yingbin Liang, H. Vincent Poor
2007	J	`jnl`	Secrecy Capacity Region of Fading Broadcast Channels CoRR Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2007	B	`conf`	Secrecy Capacity Region of Fading Broadcast Channels. ISIT Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2007	B	`conf`	Secrecy Capacity of Semi-deterministic Wire-tap Channels. ITW Jared Grubb, Sriram Vishwanath, Yingbin Liang, H. Vincent Poor
2007	J	`jnl`	Secure Communication over Fading Channels CoRR Yingbin Liang, H. Vincent Poor, Shlomo Shamai
2007	J	`jnl`	Secure Communications over Fading Channels CoRR Yingbin Liang, H. Vincent Poor
2007	J	`jnl`	Secure Nested Codes for Type II Wiretap Channels CoRR Ruoheng Liu, Yingbin Liang, H. Vincent Poor, Predrag Spasojevic
2006	Misc	`conf`	Capacity Theorems for Cooperative Relay Broadcast Channels. CISS Yingbin Liang, Gerhard Kramer
2006	J	`jnl`	Cooperative Relay Broadcast Channels CoRR Yingbin Liang, Venugopal V. Veeravalli
2006	J	`jnl`	Generalized Multiple Access Channels with Confidential Messages CoRR Yingbin Liang, H. Vincent Poor
2006	B	`conf`	Generalized Multiple Access Channels with Confidential Messages. ISIT Yingbin Liang, H. Vincent Poor
2006	J	`jnl`	Rate Regions for Relay Broadcast Channels CoRR Yingbin Liang, Gerhard Kramer
2006	J	`jnl`	The Generalized Multiple Access Channel with Confidential Messages CoRR Yingbin Liang, H. Vincent Poor
2005	J	`jnl`	Correlated MIMO wireless channels: capacity, optimal signaling, and asymptotics. IEEE Trans. Inf. Theory Venugopal V. Veeravalli, Yingbin Liang, Akbar M. Sayeed
2005	J	`jnl`	Gaussian Orthogonal Relay Channels: Optimal Resource Allocation and Capacity. IEEE Trans. Inf. Theory Yingbin Liang, Venugopal V. Veeravalli
2005	—	`—`	Multiuser Communications With Relaying and User Cooperation Yingbin Liang
2004	J	`jnl`	Capacity of noncoherent time-selective Rayleigh-fading channels. IEEE Trans. Inf. Theory Yingbin Liang, Venugopal V. Veeravalli
2004	B	`conf`	The impact of relaying on the capacity of broadcast channels. ISIT Yingbin Liang, Venugopal V. Veeravalli