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20172025
most citedNeural Certificates for Safe Control Policies

43 citations · 392 across the 82 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

cs.LG2018

Finite-Sample Analysis For Decentralized Batch Multi-Agent Reinforcement Learning With Networked Agents

Kaiqing Zhang, Zhuoran Yang, Han Liu +2

Despite the increasing interest in multi-agent reinforcement learning (MARL) in multiple communities, understanding its theoretical foundation has long been recognized as a challen…

stat.ML2018

Provable Gaussian Embedding with One Observation

Ming Yu, Zhuoran Yang, Tuo Zhao +2

The success of machine learning methods heavily relies on having an appropriate representation for data at hand. Traditionally, machine learning approaches relied on user-defined h…

cs.LG2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Jiechao Xiong, Qing Wang, Zhuoran Yang +7

Most existing deep reinforcement learning (DRL) frameworks consider either discrete action space or continuous action space solely. Motivated by applications in computer games, we…

stat.ML2018

High-dimensional Varying Index Coefficient Models via Stein's Identity

Sen Na, Zhuoran Yang, Zhaoran Wang +1

We study the parameter estimation problem for a varying index coefficient model in high dimensions. Unlike the most existing works that iteratively estimate the parameters and link…

math.ST2018

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval

Jianqing Fan, Han Liu, Zhaoran Wang +1

We study the fundamental tradeoffs between statistical accuracy and computational tractability in the analysis of high dimensional heterogeneous data. As examples, we study sparse…

math.ST2018

Tensor Methods for Additive Index Models under Discordance and Heterogeneity

Krishnakumar Balasubramanian, Jianqing Fan, Zhuoran Yang

Motivated by the sampling problems and heterogeneity issues common in high- dimensional big datasets, we consider a class of discordant additive index models. We propose method of…