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05/31/2023
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning
We examine online safe multi-agent reinforcement learning using constrai...
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07/25/2022
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
While single-agent policy optimization in a fixed environment has attrac...
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10/10/2021
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
Embedding learning has found widespread applications in recommendation s...
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05/26/2021
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale
Tremendous success of machine learning (ML) and the unabated growth in M...
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10/18/2020
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism
Data Parallelism (DP) and Model Parallelism (MP) are two common paradigm...
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08/23/2020
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning
Temporal-Difference (TD) learning with nonlinear smooth function approxi...
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06/22/2020
Beyond O(√(T)) Regret for Constrained Online Optimization: Gradual Variations and Mirror Prox
We study constrained online convex optimization, where the constraints c...
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03/05/2020
II. High Dimensional Estimation under Weak Moment Assumptions: Structured Recovery and Matrix Estimation
The purpose of this thesis is to develop new theories on high-dimensiona...
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03/02/2020
Upper Confidence Primal-Dual Optimization: Stochastically Constrained Markov Decision Processes with Adversarial Losses and Unknown Transitions
We consider online learning for episodic Markov decision processes (MDPs...
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03/01/2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
We study the Safe Reinforcement Learning (SRL) problem using the Constra...
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08/14/2019
Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis
We study the robust one-bit compressed sensing problem whose goal is to ...
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08/07/2019
Fast multi-agent temporal-difference learning via homotopy stochastic primal-dual optimization
We consider a distributed multi-agent policy evaluation problem in reinf...
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09/05/2018
Solving Non-smooth Constrained Programs with Lower Complexity than O(1/ε): A Primal-Dual Homotopy Smoothing Approach
We propose a new primal-dual homotopy smoothing algorithm for a linearly...
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04/16/2018
Structured Recovery with Heavy-tailed Measurements: A Thresholding Procedure and Optimal Rates
This paper introduces a general regularized thresholded least-square pro...
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01/17/2018
Robust Modifications of U-statistics and Applications to Covariance Estimation Problems
Let Y be a d-dimensional random vector with unknown mean μ and covarianc...
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08/12/2017