Lin F. Yang
11 papers · 2017–2026 · 9 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (23)
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Research topics
Machine Learning
(9)
Optimization & Theory Β· Machine Learning
(7)
Reinforcement Learning
(6)
Methods
(6)
Artificial Intelligence
(3)
Core AI
(3)
Learning Types Β· Machine Learning
(3)
Deep Learning
(2)
Application Areas
(2)
Core Methods
(2)
Architectures
(1)
Learning Types Β· Deep Learning
(1)
Optimization & Theory Β· Deep Learning
(1)
Keywords
sample complexity
(5)
nash equilibrium
(2)
constrained markov decision process
(2)
representation learning
(2)
multi-agent reinforcement learning
(2)
model-based reinforcement learning
(2)
generative model
(2)
regret bound
(2)
reinforcement learning
(1)
function approximation
(1)
neural network compression
(1)
natural policy gradient
(1)
global convergence
(1)
non-convex optimization
(1)
off-policy evaluation
(1)
learning theory
(1)
nearest neighbor
(1)
sample efficiency
(1)
value function
(1)
markov decision process
(1)
Papers
Sample Complexity Bounds for Linear Constrained MDPs with a Generative Model
ALT 2026
Confident Natural Policy Gradient for Local Planning in q_Ο-realizable Constrained MDPs
NeurIPS 2024
Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
NeurIPS 2024
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
JMLR 2023
Minimax sample complexity for turn-based stochastic game
UAI 2021
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation
AAAI 2021
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
ICLR 2020
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal
COLT 2020
Towards a Theoretical Understanding of Hashing-Based Neural Nets
AISTATS 2019
Clustering High Dimensional Dynamic Data Streams
ICML 2017
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
ICML 2017