Gen Li

Affiliations:
  • Chinese University of Hong Kong, Department of Statistics, Hong Kong
  • University of Pennsylvania, Wharton School, Department of Statistics and Data Science, Philadelphia, PA, USA (former)
  • Tsinghua University, Department of Electronic Engineering / TNList, Beijing, China (former)


According to our database1, Gen Li authored at least 61 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation.
IEEE Trans. Inf. Theory, August, 2024

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model.
Oper. Res., 2024

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis.
Oper. Res., 2024

A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models.
CoRR, 2024

Towards a mathematical theory for consistency training in diffusion models.
CoRR, 2024

A non-asymptotic distributional theory of approximate message passing for sparse and robust regression.
CoRR, 2024

Accelerating Convergence of Score-Based Diffusion Models, Provably.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Minimax-optimal reward-agnostic exploration in reinforcement learning.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
The Efficacy of Pessimism in Asynchronous Q-Learning.
IEEE Trans. Inf. Theory, November, 2023

Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization.
IEEE Trans. Inf. Theory, September, 2023

Towards Understanding Variation-Constrained Deep Neural Networks.
IEEE Trans. Signal Process., 2023

Softmax policy gradient methods can take exponential time to converge.
Math. Program., 2023

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models.
CoRR, 2023

Sharp high-probability sample complexities for policy evaluation with linear function approximation.
CoRR, 2023

Approximate message passing from random initialization with applications to ℤ<sub>2</sub> synchronization.
CoRR, 2023

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods.
CoRR, 2023

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction.
IEEE Trans. Inf. Theory, 2022

$\ell _1$ Regularization in Two-Layer Neural Networks.
IEEE Signal Process. Lett., 2022

Nonconvex Low-Rank Tensor Completion from Noisy Data.
Oper. Res., 2022

Multi-Agent Reinforcement Learning with Reward Delays.
CoRR, 2022

Minimax-Optimal Multi-Agent RL in Zero-Sum Markov Games With a Generative Model.
CoRR, 2022

A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models.
CoRR, 2022

Model-Based Reinforcement Learning Is Minimax-Optimal for Offline Zero-Sum Markov Games.
CoRR, 2022

Settling the Sample Complexity of Model-Based Offline Reinforcement Learning.
CoRR, 2022

Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity.
Proceedings of the International Conference on Machine Learning, 2022

2021
The Rate of Convergence of Variation-Constrained Deep Neural Networks.
CoRR, 2021

Minimax Estimation of Linear Functions of Eigenvectors in the Face of Small Eigen-Gaps.
CoRR, 2021

Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph.
Proceedings of the 38th International Conference on Machine Learning, 2021

Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Softmax Policy Gradient Methods Can Take Exponential Time to Converge.
Proceedings of the Conference on Learning Theory, 2021

2020
Unraveling the Veil of Subspace RIP Through Near-Isometry on Subspaces.
IEEE Trans. Signal Process., 2020

Lower Bound for RIP Constants and Concentration of Sum of Top Order Statistics.
IEEE Trans. Signal Process., 2020

The Efficacy of L<sub>1s</sub> Regularization in Two-Layer Neural Networks.
CoRR, 2020

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Nonconvex Low-Rank Symmetric Tensor Completion from Noisy Data.
CoRR, 2019

Subspace Estimation from Unbalanced and Incomplete Data Matrices: 𝓁<sub>2, ∞</sub> Statistical Guarantees.
CoRR, 2019

Compressed Subspace Learning Based on Canonical Angle Preserving Property.
CoRR, 2019

Johnson-Lindenstrauss Property Implies Subspace Restricted Isometry Property.
CoRR, 2019

Information Theoretic Lower Bound of Restricted Isometry Property Constant.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Restricted Isometry Property of Gaussian Random Projection for Finite Set of Subspaces.
IEEE Trans. Signal Process., 2018

An RIP-Based Performance Guarantee of Covariance-Assisted Matching Pursuit.
IEEE Signal Process. Lett., 2018

Active Orthogonal Matching Pursuit for Sparse Subspace Clustering.
IEEE Signal Process. Lett., 2018

A General Framework for Understanding Compressed Subspace Clustering Algorithms.
IEEE J. Sel. Top. Signal Process., 2018

Rigorous Restricted Isometry Property of Low-Dimensional Subspaces.
CoRR, 2018

Outage Probability Conjecture Does Not Hold for Two-Input-Multiple-Output (TIM 0) System.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Convergence Analysis on a Fast Iterative Phase Retrieval Algorithm Without Independence Assumption.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Restricted Isometry Property for Low-Dimensional Subspaces and its Application in Compressed Subspace Clustering.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Subspace Principal Angle Preserving Property of Gaussian Random Projection.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017
Linear Convergence of An Iterative Phase Retrieval Algorithm with Data Reuse.
CoRR, 2017

On the Outage Probability Conjecture for MIMO Channels.
CoRR, 2017

Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation.
CoRR, 2017

Spectral initialization for nonconvex estimation: High-dimensional limit and phase transitions.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Distance-preserving property of random projection for subspaces.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Principal angles preserving property of Gaussian random projection for subspaces.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2015
Phase retrieval using iterative projections: Dynamics in the large systems limit.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015


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