Lin Yang

papers

906

total citations

papers (28)

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

NEURIPS 2020arXiv

133

citations

On Reward-Free Reinforcement Learning with Linear Function Approximation

NEURIPS 2020arXiv

114

citations

Toward the Fundamental Limits of Imitation Learning

NEURIPS 2020arXiv

108

citations

Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification

CVPR 2023arXiv

citations

PathAsst: A Generative Foundation AI Assistant towards Artificial General Intelligence of Pathology

AAAI 2024arXiv

citations

Preference-based Reinforcement Learning with Finite-Time Guarantees

NEURIPS 2020arXiv

citations

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification

ECCV 2024arXiv

citations

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension

NEURIPS 2020arXiv

citations

Near-Optimal Sample Complexity Bounds for Constrained MDPs

NEURIPS 2022arXiv

citations

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

ECCV 2024arXiv

citations

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

CVPR 2025arXiv

citations

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds

NEURIPS 2023arXiv

citations

Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

NEURIPS 2021arXiv

citations

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs

NEURIPS 2021arXiv

citations

DPA-P2PNet: Deformable Proposal-Aware P2PNet for Accurate Point-Based Cell Detection

AAAI 2024arXiv

citations

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning

NEURIPS 2020arXiv

citations

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs

NEURIPS 2023arXiv

citations

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback

NEURIPS 2021

citations

Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images

CVPR 2022

citations

Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context

NEURIPS 2022

citations

Is Long Horizon RL More Difficult Than Short Horizon RL?

NEURIPS 2020

citations

Transfer Q-Learning with Composite MDP Structures

ICML 2025

citations

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination

NEURIPS 2023

citations

Planning with General Objective Functions: Going Beyond Total Rewards

NEURIPS 2020

citations

On the Value of Interaction and Function Approximation in Imitation Learning

NEURIPS 2021

citations

Lin Yang

papers (28)

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

On Reward-Free Reinforcement Learning with Linear Function Approximation

Toward the Fundamental Limits of Imitation Learning

Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification

PathAsst: A Generative Foundation AI Assistant towards Artificial General Intelligence of Pathology

Preference-based Reinforcement Learning with Finite-Time Guarantees

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension

Near-Optimal Sample Complexity Bounds for Constrained MDPs

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Replicability in Reinforcement Learning

Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning

Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds

Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs

DPA-P2PNet: Deformable Proposal-Aware P2PNet for Accurate Point-Based Cell Detection

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback

Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images

Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context

Is Long Horizon RL More Difficult Than Short Horizon RL?

Transfer Q-Learning with Composite MDP Structures

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination

Planning with General Objective Functions: Going Beyond Total Rewards

On the Value of Interaction and Function Approximation in Imitation Learning

papers (28)

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

On Reward-Free Reinforcement Learning with Linear Function Approximation

Toward the Fundamental Limits of Imitation Learning

Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification

PathAsst: A Generative Foundation AI Assistant towards Artificial General Intelligence of Pathology

Preference-based Reinforcement Learning with Finite-Time Guarantees

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension

Near-Optimal Sample Complexity Bounds for Constrained MDPs

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Replicability in Reinforcement Learning

Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning

Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds

Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs

DPA-P2PNet: Deformable Proposal-Aware P2PNet for Accurate Point-Based Cell Detection

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback

Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images

Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context

Is Long Horizon RL More Difficult Than Short Horizon RL?

Transfer Q-Learning with Composite MDP Structures

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination

Planning with General Objective Functions: Going Beyond Total Rewards

On the Value of Interaction and Function Approximation in Imitation Learning