Zeyu Zheng | DeepAI

DeepAI AI Chat

Featured Co-authors

Michael I. Jordan
283 publications
Xiaodan Liang
197 publications
Eric P Xing
147 publications
Razvan Pascanu
87 publications
Marco Cuturi
70 publications
Wei Dai
62 publications
Feng Zhu
59 publications
Pengtao Xie
59 publications
Hao Zhang
58 publications
Manuela Veloso
57 publications
Satinder Singh
56 publications

∙ 04/10/2023

Regret Distribution in Stochastic Bandits: Optimal Trade-off between Expectation and Tail Risk

We study the trade-off between expectation and tail risk for regret dist...

0 David Simchi-Levi, et al. ∙

∙ 04/08/2023

Best Arm Identification with Fairness Constraints on Subpopulations

We formulate, analyze and solve the problem of best arm identification w...

0 Yuhang Wu, et al. ∙

∙ 03/02/2023

Understanding plasticity in neural networks

Plasticity, the ability of a neural network to quickly change its predic...

0 Clare Lyle, et al. ∙

∙ 11/26/2022

Efficient Targeted Learning of Heterogeneous Treatment Effects for Multiple Subgroups

In biomedical science, analyzing treatment effect heterogeneity plays an...

0 Waverly Wei, et al. ∙

∙ 10/13/2022

Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations

We study a game between liquidity provider and liquidity taker agents in...

0 Nelson Vadori, et al. ∙

∙ 10/13/2022

Adaptive A/B Tests and Simultaneous Treatment Parameter Optimization

Constructing asymptotically valid confidence intervals through a valid c...

0 Yuhang Wu, et al. ∙

∙ 09/12/2022

Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization

Nonsmooth nonconvex optimization problems broadly emerge in machine lear...

28 Tianyi Lin, et al. ∙

∙ 06/23/2022

Inference on the Best Policies with Many Covariates

Understanding the impact of the most effective policies or treatments on...

0 Waverly Wei, et al. ∙

∙ 06/07/2022

A Simple and Optimal Policy Design with Safety against Heavy-tailed Risk for Multi-armed Bandits

We design new policies that ensure both worst-case optimality for expect...

0 David Simchi-Levi, et al. ∙

∙ 02/08/2022

GrASP: Gradient-Based Affordance Selection for Planning

Planning with a learned model is arguably a key component of intelligenc...

0 Vivek Veeriah, et al. ∙

∙ 01/09/2022

Selecting the Best Optimizing System

We formulate selecting the best optimizing system (SBOS) problems and pr...

0 Nian Si, et al. ∙

∙ 06/28/2021

Dynamic Planning and Learning under Recovering Rewards

Motivated by emerging applications such as live-streaming e-commerce, pr...

0 David Simchi-Levi, et al. ∙

∙ 03/27/2021

Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization

Conditional Generative Adversarial Networks are known to be difficult to...

0 Yufeng Zheng, et al. ∙

∙ 02/09/2021

Pairwise Weights for Temporal Credit Assignment

How much credit (or blame) should an action taken in a state get for a f...

0 Zeyu Zheng, et al. ∙

∙ 02/09/2021

Learning State Representations from Random Deep Action-conditional Predictions

In this work, we study auxiliary prediction tasks defined by temporal-di...

0 Zeyu Zheng, et al. ∙

∙ 12/27/2020

Doubly Stochastic Generative Arrivals Modeling

We propose a new framework named DS-WGAN that integrates the doubly stoc...

0 Yufeng Zheng, et al. ∙

∙ 06/22/2020

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

Optimal transport (OT) distances are increasingly used as loss functions...

0 Tianyi Lin, et al. ∙

∙ 06/21/2020

Automated Optical Multi-layer Design via Deep Reinforcement Learning

Optical multi-layer thin films are widely used in optical and energy app...

0 Haozhu Wang, et al. ∙

∙ 12/11/2019

What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as ...

25 Zeyu Zheng, et al. ∙

∙ 05/13/2019

Ques-Chain: an Ethereum Based E-Voting System

Ethereum is an open-source, public, blockchain-based distributed computi...

0 Qixuan Zhang, et al. ∙

∙ 04/17/2018

On Learning Intrinsic Rewards for Policy Gradient Methods

In many sequential decision making tasks, it is challenging to design re...

0 Zeyu Zheng, et al. ∙

∙ 06/11/2017

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

Deep learning models can take weeks to train on a single GPU-equipped ma...

0 Hao Zhang, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world