Yingbin Liang - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 100 from 194

2024

AI-EDGE: An NSF AI institute for future edge networks and distributed intelligencePeizhong Ju, Chengzhang Li, Yingbin Liang, Ness B. Shroff. aim, 45(1):29-34, 2024. [doi]

2023

Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex OptimizationZiyi Chen 0002, Yi Zhou 0017, Yingbin Liang, Zhaosong Lu. icml 2023: 5396-5427 [doi]

Global Convergence of Two-Timescale Actor-Critic for Solving Linear Quadratic RegulatorXuyang Chen, Jingliang Duan, Yingbin Liang, Lin Zhao 0009. AAAI 2023: 7087-7095 [doi]

Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPsYuan Cheng, Ruiquan Huang, Yingbin Liang, Jing Yang 0002. iclr 2023: [doi]

Provably Efficient Algorithm for Nonstationary Low-Rank MDPsYuan Cheng, Jing Yang, Yingbin Liang. nips 2023: [doi]

Non-stationary Reinforcement Learning under General Function ApproximationSongtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang 0002, Yingbin Liang. icml 2023: 9976-10007 [doi]

Online Nonconvex Optimization with Limited Instantaneous Oracle FeedbackZiwei Guan, Yi Zhou 0017, Yingbin Liang. colt 2023: 3328-3355 [doi]

Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RLRuiquan Huang, Jing Yang 0002, Yingbin Liang. iclr 2023: [doi]

Lower Bounds and Accelerated Algorithms for Bilevel OptimizationKaiyi Ji, Yingbin Liang. jmlr, 24, 2023. [doi]

Theoretical Characterization of the Generalization Performance of Overfitted Meta-LearningPeizhong Ju, Yingbin Liang, Ness B. Shroff. iclr 2023: [doi]

Non-Convex Bilevel Optimization with Time-Varying Objective FunctionsSen Lin, Daouda Sow, Kaiyi Ji, Yingbin Liang, Ness B. Shroff. nips 2023: [doi]

Theory on Forgetting and Generalization of Continual LearningSen Lin, Peizhong Ju, Yingbin Liang, Ness B. Shroff. icml 2023: 21078-21100 [doi]

A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard ConstraintsMing Shi, Yingbin Liang, Ness B. Shroff. icml 2023: 31243-31268 [doi]

Near-Optimal Adversarial Reinforcement Learning with Switching CostsMing Shi, Yingbin Liang, Ness B. Shroff. iclr 2023: [doi]

Learning to Generalize Provably in Learning to OptimizeJunjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang. aistats 2023: 9807-9825 [doi]

M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-AdaptationJunjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang. iclr 2023: [doi]

2022

Self-Secure Capacity-Achieving Feedback Schemes of Gaussian Multiple-Access Wiretap Channels With Degraded Message SetsBin Dai 0003, Chong Li, Yingbin Liang, Zheng Ma 0001, Shlomo Shamai. tifs, 17:1583-1596, 2022. [doi]

Understanding generalization error of SGD in nonconvex optimizationYi Zhou 0017, Yingbin Liang, Huishuai Zhang. ml, 111(1):345-375, 2022. [doi]

Provable Benefit of Multitask Representation Learning in Reinforcement LearningYuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang. nips 2022: [doi]

PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning MethodZiwei Guan, Tengyu Xu, Yingbin Liang. iclr 2022: [doi]

Provable Generalization of Overparameterized Meta-learning Trained with SGDYu Huang, Yingbin Liang, Longbo Huang. nips 2022: [doi]

Theoretical Convergence of Multi-Step Model-Agnostic Meta-LearningKaiyi Ji, Junjie Yang, Yingbin Liang. jmlr, 23, 2022. [doi]

Will Bilevel Optimizers Benefit from LoopsKaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying. nips 2022: [doi]

Model-Based Offline Meta-Reinforcement Learning with RegularizationSen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang. iclr 2022: [doi]

Data sampling affects the complexity of online SGD over dependent dataShaocong Ma, Ziyi Chen 0002, Yi Zhou 0017, Kaiyi Ji, Yingbin Liang. uai 2022: 1296-1305 [doi]

On the Convergence Theory for Hessian-Free Bilevel AlgorithmsDaouda Sow, Kaiyi Ji, Yingbin Liang. nips 2022: [doi]

Deterministic policy gradient: Convergence analysisHuaqing Xiong, Tengyu Xu, Lin Zhao 0009, Yingbin Liang, Wei Zhang 0013. uai 2022: 2159-2169 [doi]

A Unifying Framework of Off-Policy General Value Function EvaluationTengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang. nips 2022: [doi]

2021

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ GeometryZiyi Chen 0002, Yi Zhou, Tengyu Xu, Yingbin Liang. iclr 2021: [doi]

Faster Non-asymptotic Convergence for Double Q-learningLin Zhao 0009, Huaqing Xiong, Yingbin Liang. nips 2021: 7242-7253 [doi]

When Will Generative Adversarial Imitation Learning Algorithms Attain Global ConvergenceZiwei Guan, Tengyu Xu, Yingbin Liang. aistats 2021: 1117-1125 [doi]

Understanding Estimation and Generalization Error of Generative Adversarial NetworksKaiyi Ji, Yi Zhou, Yingbin Liang. TIT, 67(5):3114-3129, 2021. [doi]

Bilevel Optimization: Convergence Analysis and Enhanced DesignKaiyi Ji, Junjie Yang, Yingbin Liang. icml 2021: 4882-4892 [doi]

MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific DataQunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney. simods, 3(4):1197-1222, 2021. [doi]

Finite-time theory for momentum Q-learningBowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang. uai 2021: 665-674 [doi]

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian SamplingHuaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang. AAAI 2021: 10460-10468 [doi]

Doubly Robust Off-Policy Actor-Critic: Convergence and OptimalityTengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang. icml 2021: 11581-11591 [doi]

Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning AlgorithmsTengyu Xu, Yingbin Liang. aistats 2021: 811-819 [doi]

CRPO: A New Approach for Safe Reinforcement Learning with Convergence GuaranteeTengyu Xu, Yingbin Liang, Guanghui Lan. icml 2021: 11480-11491 [doi]

Provably Faster Algorithms for Bilevel OptimizationJunjie Yang, Kaiyi Ji, Yingbin Liang. nips 2021: 13670-13682 [doi]

2020

Impact of Action-Dependent State and Channel Feedback on Gaussian Wiretap ChannelsBin Dai 0003, Chong Li, Yingbin Liang, Zheng Ma 0001, Shlomo Shamai Shitz. TIT, 66(6):3435-3455, 2020. [doi]

Enhancing physical layer security via channel feedback: a surveyBin Dai 0003, Chong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai (Shitz). ejwcn, 2020(1):58, 2020. [doi]

On the Capacity of Gaussian Multiple-Access Wiretap Channels with FeedbackBin Dai 0003, Chong Li, Yingbin Liang, Zheng Ma 0001, Shlomo Shamai Shitz. isita 2020: 397-401 [doi]

Feedback Capacity of Gaussian Multiple-Access Wiretap Channel with Degraded Message SetsBin Dai 0003, Chong Li, Yingbin Liang, Zheng Ma 0001, Shlomo Shamai Shitz. itw 2021: 1-5 [doi]

Guaranteed Recovery of One-Hidden-Layer Neural Networks via Cross EntropyHaoyu Fu, Yuejie Chi, Yingbin Liang. tsp, 68:3225-3235, 2020. [doi]

Robust Dynamic Spectrum Access in Adversarial EnvironmentsZiwei Guan, Timothy Y. Hu, Joseph Palombo, Michael J. Liston, Donald J. Bucci, Yingbin Liang. icc 2020: 1-7 [doi]

Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial AttackZiwei Guan, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, Yingbin Liang. AAAI 2020: 4036-4043 [doi]

Convergence of Meta-Learning with Task-Specific Adaptation over Partial ParametersKaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor. nips 2020: [doi]

History-Gradient Aided Batch Size Adaptation for Variance Reduced AlgorithmsKaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang. icml 2020: 4762-4772 [doi]

Spectral Algorithms for Community Detection in Directed NetworksZhe Wang, Yingbin Liang, Pengsheng Ji. jmlr, 21, 2020. [doi]

Analysis of Q-learning with Adaptation and Momentum Restart for Gradient DescentBowen Weng, Huaqing Xiong, Yingbin Liang, Wei Zhang. IJCAI 2020: 3051-3057 [doi]

Finite-Time Analysis for Double Q-learningHuaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang. nips 2020: [doi]

Reanalysis of Variance Reduced Temporal Difference LearningTengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang. iclr 2020: [doi]

Improving Sample Complexity Bounds for (Natural) Actor-Critic AlgorithmsTengyu Xu, Zhe Wang, Yingbin Liang. nips 2020: [doi]

Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex OptimizationYi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh. IJCAI 2020: 1445-1451 [doi]

2019

The Dirty Paper Wiretap Feedback Channel with or without Action on the StateBin Dai 0003, Chong Li, Yingbin Liang, Zheng Ma, Shlomo Shamai Shitz. isit 2019: 657-661 [doi]

MIMO Gaussian State-Dependent Channels with a State-Cognitive HelperMichael Dikshtein, Ruchen Duan, Yingbin Liang, Shlomo Shamai (Shitz). entropy, 21(3):273, 2019. [doi]

Local Geometry of Cross Entropy Loss in Learning One-Hidden-Layer Neural NetworksHaoyu Fu, Yuejie Chi, Yingbin Liang. isit 2019: 1972-1976 [doi]

Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex OptimizationKaiyi Ji, Zhe Wang, Yi Zhou, Yingbin Liang. icml 2019: 3100-3109 [doi]

Secrecy Capacity of Colored Gaussian Noise Channels With FeedbackChong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai Shitz. TIT, 65(9):5771-5782, 2019. [doi]

Distributed SGD Generalizes Well Under AsynchronyJayanth Regatti, Gaurav Tendolkar, Yi Zhou, Abhishek Gupta, Yingbin Liang. allerton 2019: 863-870 [doi]

State-Dependent Interference Channel With Correlated StatesYunhao Sun, Ruchen Duan, Yingbin Liang, Shlomo Shamai Shitz. TIT, 65(7):4518-4531, 2019. [doi]

A note on inexact gradient and Hessian conditions for cubic regularized Newton's methodZhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan. orl, 47(2):146-149, 2019. [doi]

SpiderBoost and Momentum: Faster Variance Reduction AlgorithmsZhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh. nips 2019: 2403-2413 [doi]

Stochastic Variance-Reduced Cubic Regularization for Nonconvex OptimizationZhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan. aistats 2019: 2731-2740 [doi]

Cubic Regularization with Momentum for Nonconvex OptimizationZhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan. uai 2018: 118 [doi]

K-Medoids Clustering of Data Sequences With Composite DistributionsTiexing Wang, Qunwei Li, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney. tsp, 67(8):2093-2106, 2019. [doi]

Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian SamplesTengyu Xu, Shaofeng Zou, Yingbin Liang. nips 2019: 10633-10643 [doi]

A simple convergence analysis of Bregman proximal gradient algorithmYi Zhou, Yingbin Liang, Lixin Shen. coap, 73(3):903-912, 2019. [doi]

SGD Converges to Global Minimum in Deep Learning via Star-convex PathYi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh. iclr 2019: [doi]

Finite-Sample Analysis for SARSA with Linear Function ApproximationShaofeng Zou, Tengyu Xu, Yingbin Liang. nips 2019: 8665-8675 [doi]

2018

State-Dependent Gaussian Multiple Access Channels: New Outer Bounds and Capacity ResultsWei Yang 0001, Yingbin Liang, Shlomo Shamai Shitz, H. Vincent Poor. TIT, 64(12):7866-7882, 2018. [doi]

Estimation of KL Divergence: Optimal Minimax RateYuheng Bu, Shaofeng Zou, Yingbin Liang, Venugopal V. Veeravalli. TIT, 64(4):2648-2674, 2018. [doi]

Minimax Estimation of Neural Net DistanceKaiyi Ji, Yingbin Liang. nips 2018: 3849-3858 [doi]

A Coding Scheme for Colored Gaussian Wiretap Channels with FeedbackChong Li, Yingbin Liang, H. Vincent Poor, Shlomo Shamai. isit 2018: 131-135 [doi]

Nonparametric Composite Hypothesis Testing in an Asymptotic RegimeQunwei Li, Tiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney. jstsp, 12(5):1005-1014, 2018. [doi]

Data-Driven Nonparametric Hypothesis TestingYixian Liu, Yingbin Liang, Shuguang Cui. icassp 2018: 4234-4238 [doi]

Data-Driven Nonparametric Existence and Association ProblemsYixian Liu, Yingbin Liang, Shuguang Cui. tsp, 66(24):6377-6389, 2018. [doi]

Clustering under composite generative modelsTiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney. ciss 2018: 1-6 [doi]

Exponentially Consistent K-Means Clustering Algorithm Based on Kolmogrov-Smirnov TestTiexing Wang, Donald J. Bucci, Yingbin Liang, Biao Chen, Pramod K. Varshney. icassp 2018: 2296-2300 [doi]

Median-Truncated Nonconvex Approach for Phase Retrieval With OutliersHuishuai Zhang, Yuejie Chi, Yingbin Liang. TIT, 64(11):7287-7310, 2018. [doi]

Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer ClustersYi Zhou, Yingbin Liang, Yaoliang Yu, Wei Dai 0003, Eric P. Xing. jmlr, 19, 2018. [doi]

Convergence of Cubic Regularization for Nonconvex Optimization under KL PropertyYi Zhou, Zhe Wang, Yingbin Liang. nips 2018: 3764-3773 [doi]

Critical Points of Linear Neural Networks: Analytical Forms and Landscape PropertiesYi Zhou, Yingbin Liang. iclr 2018: [doi]

Degraded Broadcast Channel With Secrecy Outside a Bounded RangeShaofeng Zou, Yingbin Liang, Lifeng Lai, H. Vincent Poor, Shlomo Shamai Shitz. TIT, 64(3):2104-2120, 2018. [doi]

2017

Outer bounds for Gaussian multiple access channels with state known at one encoderWei Yang 0001, Yingbin Liang, Shlomo Shamai Shitz, H. Vincent Poor. isit 2017: 869-873 [doi]

On the Sum-Rate Capacity of Poisson MISO Multiple Access ChannelsAin Ul Aisha, Lifeng Lai, Yingbin Liang, Shlomo Shamai Shitz. TIT, 63(10):6457-6473, 2017. [doi]

Sum-Rate Capacity of Poisson MIMO Multiple-Access ChannelsAin Ul Aisha, Lifeng Lai, Yingbin Liang, Shlomo Shamai Shitz. tcom, 65(11):4765-4776, 2017. [doi]

Secrecy capacity of the first-order autoregressive moving average Gaussian channel with feedbackChong Li, Yingbin Liang. isit 2017: 1963-1967 [doi]

Convergence Analysis of Proximal Gradient with Momentum for Nonconvex OptimizationQunwei Li, Yi Zhou, Yingbin Liang, Pramod K. Varshney. icml 2017: 2111-2119 [doi]

State-dependent Z-interference channel with correlated statesYunhao Sun, Yingbin Liang, Ruchen Duan, Shlomo Shamai Shitz. isit 2017: 644-648 [doi]

A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental AlgorithmsHuishuai Zhang, Yingbin Liang, Yuejie Chi. jmlr, 18, 2017. [doi]

Multi-Key Generation Over a Cellular Model With a HelperHuishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai Shitz. TIT, 63(6):3804-3822, 2017. [doi]

Demixing sparse signals via convex optimizationYi Zhou, Yingbin Liang. icassp 2017: 4202-4206 [doi]

Nonparametric Detection of Anomalous Data StreamsShaofeng Zou, Yingbin Liang, H. Vincent Poor, Xinghua Shi. tsp, 65(21):5785-5797, 2017. [doi]

Nonparametric Detection of Geometric Structures Over NetworksShaofeng Zou, Yingbin Liang, H. Vincent Poor. tsp, 65(19):5034-5046, 2017. [doi]

Gaussian fading channel with secrecy outside a bounded rangeShaofeng Zou, Yingbin Liang, Shlomo Shamai. cns 2017: 545-549 [doi]

2016

State-Dependent Gaussian Interference Channels: Can State Be Fully Canceled?Ruchen Duan, Yingbin Liang, Shlomo Shamai Shitz. TIT, 62(4):1957-1970, 2016. [doi]

Capacity Characterization for State-Dependent Gaussian Channel With a HelperYunhao Sun, Ruchen Duan, Yingbin Liang, Ashish Khisti, Shlomo Shamai Shitz. TIT, 62(12):7123-7134, 2016. [doi]

All Publications

Filter by Year

[-]
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Tag
OR AND NOT 1

Filter by Venue

[+]
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1

Researchr

Publications by 'Yingbin Liang'

Viewing Publication 1 - 100 from 194

2024

2023

2022

2021

2020

2019

2018

2017

2016

All Publications

Filter by Year [-]OR AND NOT 1

Filter by TypeOR AND NOT 1

Filter by TagOR AND NOT 1

Filter by Venue [+]OR AND NOT 1

Filter by Author [+]OR AND NOT 1

Filter by Top Terms [+]OR AND NOT 1

Researchr

Publications by 'Yingbin Liang'

Viewing Publication 1 - 100 from 194

2024

2023

2022

2021

2020

2019

2018

2017

2016

Filter by Year

[-]
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Tag
OR AND NOT 1

Filter by Venue

[+]
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1