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Lin Yang
ORCID
Publication Activity (10 Years)
Years Active: 2018-2023
Publications (10 Years): 31
Top Topics
Sample Complexity
Markov Decision Processes
Reinforcement Learning
Action Space
Top Venues
NeurIPS
ICML
AISTATS
CoRR
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Publications
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Osama A. Hanna
,
Lin Yang
,
Christina Fragouli
Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination.
NeurIPS
(2023)
Jiayi Huang
,
Han Zhong
,
Liwei Wang
,
Lin Yang
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds.
NeurIPS
(2023)
Masoud Monajatipoor
,
Liunian Harold Li
,
Mozhdeh Rouhsedaghat
,
Lin Yang
,
Kai-Wei Chang
MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models.
ACL (2)
(2023)
Osama A. Hanna
,
Lin Yang
,
Christina Fragouli
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms.
COLT
(2023)
Sanae Amani
,
Tor Lattimore
,
András György
,
Lin Yang
Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost.
ICML
(2023)
Jialin Dong
,
Lin Yang
Does Sparsity Help in Learning Misspecified Linear Bandits?
ICML
(2023)
Sanae Amani
,
Lin Yang
,
Ching-An Cheng
Provably Efficient Lifelong Reinforcement Learning with Linear Representation.
ICLR
(2023)
Amin Karbasi
,
Grigoris Velegkas
,
Lin Yang
,
Felix Zhou
Replicability in Reinforcement Learning.
NeurIPS
(2023)
Dingwen Kong
,
Lin Yang
Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning.
NeurIPS
(2022)
Weichao Mao
,
Lin Yang
,
Kaiqing Zhang
,
Tamer Basar
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning.
ICML
(2022)
Ningyuan Huang
,
Soledad Villar
,
Carey E. Priebe
,
Da Zheng
,
Chengyue Huang
,
Lin Yang
,
Vladimir Braverman
From Local to Global: Spectral-Inspired Graph Neural Networks.
CoRR
(2022)
Jingfeng Wu
,
Vladimir Braverman
,
Lin Yang
Gap-Dependent Unsupervised Exploration for Reinforcement Learning.
AISTATS
(2022)
Osama A. Hanna
,
Lin Yang
,
Christina Fragouli
Solving Multi-Arm Bandit Using a Few Bits of Communication.
AISTATS
(2022)
Sharan Vaswani
,
Lin Yang
,
Csaba Szepesvári
Near-Optimal Sample Complexity Bounds for Constrained MDPs.
NeurIPS
(2022)
Osama A. Hanna
,
Lin Yang
,
Christina Fragouli
Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context.
NeurIPS
(2022)
Xiaoyu Chen
,
Jiachen Hu
,
Lin Yang
,
Liwei Wang
Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver.
ICLR
(2022)
Fei Feng
,
Wotao Yin
,
Alekh Agarwal
,
Lin Yang
Provably Correct Optimization and Exploration with Non-linear Policies.
ICML
(2021)
Sanae Amani
,
Christos Thrampoulidis
,
Lin Yang
Safe Reinforcement Learning with Linear Function Approximation.
ICML
(2021)
Han Zhong
,
Jiayi Huang
,
Lin Yang
,
Liwei Wang
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs.
NeurIPS
(2021)
Jingfeng Wu
,
Vladimir Braverman
,
Lin Yang
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning.
NeurIPS
(2021)
Nived Rajaraman
,
Yanjun Han
,
Lin Yang
,
Jingbo Liu
,
Jiantao Jiao
,
Kannan Ramchandran
On the Value of Interaction and Function Approximation in Imitation Learning.
NeurIPS
(2021)
Zeyu Jia
,
Lin Yang
,
Csaba Szepesvári
,
Mengdi Wang
Model-Based Reinforcement Learning with Value-Targeted Regression.
L4DC
(2020)
Alex Ayoub
,
Zeyu Jia
,
Csaba Szepesvári
,
Mengdi Wang
,
Lin Yang
Model-Based Reinforcement Learning with Value-Targeted Regression.
ICML
(2020)
Yingyu Liang
,
Zhao Song
,
Mengdi Wang
,
Lin Yang
,
Xin Yang
Sketching Transformed Matrices with Applications to Natural Language Processing.
AISTATS
(2020)
Aaron Sidford
,
Mengdi Wang
,
Lin Yang
,
Yinyu Ye
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity.
AISTATS
(2020)
Jingfeng Wu
,
Vladimir Braverman
,
Lin Yang
Obtaining Adjustable Regularization for Free via Iterate Averaging.
ICML
(2020)
Lin Yang
,
Mengdi Wang
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.
ICML
(2020)
Lin Yang
,
Mengdi Wang
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features.
ICML
(2019)
Minshuo Chen
,
Lin Yang
,
Mengdi Wang
,
Tuo Zhao
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization.
NeurIPS
(2018)
Aaron Sidford
,
Mengdi Wang
,
Xian Wu
,
Lin Yang
,
Yinyu Ye
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model.
NeurIPS
(2018)
Minshuo Chen
,
Lin Yang
,
Mengdi Wang
,
Tuo Zhao
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization.
CoRR
(2018)