Banghua Zhu | DeepAI

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Sergey Levine
379 publications
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Shuai Wang
157 publications
Masayoshi Tomizuka
149 publications
Dawn Song
130 publications
Martin J. Wainwright
102 publications
Wei Zhan
79 publications
Yao Lu
73 publications
Stuart Russell
64 publications
Jacob Steinhardt
58 publications
Chenguang Zhu
57 publications

∙ 09/18/2023

Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration

Safe Reinforcement Learning (RL) aims to find a policy that achieves hig...

0 Jinning Li, et al. ∙

∙ 09/07/2023

Noisy Computing of the 𝖮𝖱 and 𝖬𝖠𝖷 Functions

We consider the problem of computing a function of n variables using noi...

0 Banghua Zhu, et al. ∙

∙ 06/21/2023

On the Optimal Bounds for Noisy Computing

We revisit the problem of computing with noisy information considered in...

0 Banghua Zhu, et al. ∙

∙ 06/04/2023

Fine-Tuning Language Models with Advantage-Induced Policy Alignment

Reinforcement learning from human feedback (RLHF) has emerged as a relia...

0 Banghua Zhu, et al. ∙

∙ 06/03/2023

On Optimal Caching and Model Multiplexing for Large Model Inference

Large Language Models (LLMs) and other large foundation models have achi...

0 Banghua Zhu, et al. ∙

∙ 06/01/2023

Doubly Robust Self-Training

Self-training is an important technique for solving semi-supervised lear...

0 Banghua Zhu, et al. ∙

∙ 05/19/2023

Online Learning in a Creator Economy

The creator economy has revolutionized the way individuals can profit th...

0 Banghua Zhu, et al. ∙

∙ 01/27/2023

Online Learning in Stackelberg Games with an Omniscient Follower

We study the problem of online learning in a two-player decentralized co...

0 Geng Zhao, et al. ∙

∙ 01/26/2023

Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons

We provide a theoretical framework for Reinforcement Learning with Human...

0 Banghua Zhu, et al. ∙

∙ 05/24/2022

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees

We propose Byzantine-robust federated learning protocols with nearly opt...

7 Banghua Zhu, et al. ∙

∙ 04/05/2022

Jump-Start Reinforcement Learning

Reinforcement learning (RL) provides a theoretical framework for continu...

0 Ikechukwu Uchendu, et al. ∙

∙ 02/02/2022

Robust Estimation for Nonparametric Families via Generative Adversarial Networks

We provide a general framework for designing Generative Adversarial Netw...

9 Banghua Zhu, et al. ∙

∙ 03/22/2021

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism

Offline (or batch) reinforcement learning (RL) algorithms seek to learn ...

41 Paria Rashidinejad, et al. ∙

∙ 01/19/2021

Minimax Off-Policy Evaluation for Multi-Armed Bandits

We study the problem of off-policy evaluation in the multi-armed bandit ...

0 Cong Ma, et al. ∙

∙ 01/12/2021

Linear Representation Meta-Reinforcement Learning for Instant Adaptation

This paper introduces Fast Linearized Adaptive Policy (FLAP), a new meta...

0 Matt Peng, et al. ∙

∙ 05/28/2020

Robust estimation via generalized quasi-gradients

We explore why many recently proposed robust estimation problems are eff...

0 Banghua Zhu, et al. ∙

∙ 01/21/2020

When does the Tukey median work?

We analyze the performance of the Tukey median estimator under total var...

0 Banghua Zhu, et al. ∙

∙ 09/19/2019

Generalized Resilience and Robust Statistics

Robust statistics traditionally focuses on outliers, or perturbations in...

0 Banghua Zhu, et al. ∙

∙ 01/27/2019

Deconstructing Generative Adversarial Networks

We deconstruct the performance of GANs into three components: 1. Formu...

0 Banghua Zhu, et al. ∙

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