Yuandong Tian

RESEARCH SCIENTIST | MENLO PARK, UNITED STATES

Yuandong is a Research Scientist working on deep reinforcement learning and its applications on games, and theoretical analysis of deep models. He is the Lead Scientist and Engineer for ELF OpenGo and DarkForest Go project. Prior to that, he was a researcher and engineer on the Google Self-driving Car team. Yann received a Ph.D. in Robotics Institute, Carnegie Mellon University, and a Bachelor's and Master's degree of Computer Science in Shanghai Jiao Tong University. He is the recipient of ICCV 2013 Marr Prize Honorable Mentions.

Yuandong's Work

Yuandong's Publications

August 12, 2024

CORE MACHINE LEARNING

Contrastive Predict-and-Search for Mixed Integer Linear Programs

Arman Zharmagambetov, Yuandong Tian, Aaron Ferber, Bistra Dilkina, Taoan Huang

August 12, 2024

August 02, 2024

CORE MACHINE LEARNING

GenCO: Generating Diverse Designs with Combinatorial Constraints

Arman Zharmagambetov, Yuandong Tian

August 02, 2024

March 13, 2024

CORE MACHINE LEARNING

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

March 13, 2024

July 26, 2023

SYSTEMS RESEARCH

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction

Youwei Liang, Kevin Stone, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Pengtao Xie, Hugh Leather, Yuandong Tian

July 26, 2023

October 14, 2022

CORE MACHINE LEARNING

SYSTEMS RESEARCH

Latent Execution for Neural Program Synthesis

Yuandong Tian, Dawn Song, Xinyun Chen

October 14, 2022

October 14, 2022

RESEARCH

Understanding Deep Contrastive Learning via Coordinate-wise Optimization

Yuandong Tian

October 14, 2022

July 07, 2022

On the Importance of Asymmetry for Siamese Representation Learning

Xinlei Chen, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xiao Wang

July 07, 2022

July 01, 2022

Denoised MDPs: Learning World Models Better Than the World Itself

Yuandong Tian, Amy Zhang, Simon Shaolei Du, Antonio Torralba, Phillip Isola, Tongzhou Wang

July 01, 2022

November 02, 2021

REINFORCEMENT LEARNING

CORE MACHINE LEARNING

Learning Search Space Partition for Path Planning

Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian

November 02, 2021

November 01, 2021

CORE MACHINE LEARNING

SYSTEMS RESEARCH

Latent Execution for Neural Program Synthesis

Xinyun Chen, Dawn Song, Yuandong Tian

November 01, 2021

November 01, 2021

REINFORCEMENT LEARNING

NovelD: A Simple yet Effective Exploration Criterion

Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian

November 01, 2021

November 01, 2021

REINFORCEMENT LEARNING

MADE: Exploration via Maximizing Deviation from Explored Regions

Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez, Stuart Russell

November 01, 2021

June 22, 2021

REINFORCEMENT LEARNING

SYSTEMS RESEARCH

Coda: An End-to-End Neural Program Decompiler

Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao

June 22, 2021

December 02, 2020

REINFORCEMENT LEARNING

CORE MACHINE LEARNING

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

Yuandong Tian, Linnan Wang, Rodrigo Fonseca

December 02, 2020

August 01, 2020

ML APPLICATIONS

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction

Dehua Cheng, Eric Zhou, Jiyan Yang, Yuandong Tian, Qingquan Song, Xia Hu

August 01, 2020

December 03, 2019

RESEARCH

COMPUTER VISION

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers

Ari Morcos, Haonan Yu, Michela Paganini, Yuandong Tian

December 03, 2019

May 30, 2019

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero

Jerry Ma, James Pinkerton, Larry Zitnick, Qucheng Gong, Shubho Sengupta, Yuandong Tian, Zhuoyuan Chen

May 30, 2019

May 03, 2019

RESEARCH

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

Yuandong Tian, Huazhe Xu, Tengyu Ma, Trevor Darrell, Yuanzhi Li, Yuping Luo

May 03, 2019

May 01, 2019

RESEARCH

COMPUTER VISION

M3RL: MIND-AWARE MULTI-AGENT MANAGEMENT REINFORCEMENT LEARNING

Yuandong Tian, Tianmin Shu

May 01, 2019