Jason D. Lee

Jason D. Lee

Princeton University

H-index: 57

North America-United States

About Jason D. Lee

Jason D. Lee, With an exceptional h-index of 57 and a recent h-index of 53 (since 2020), a distinguished researcher at Princeton University, specializes in the field of Machine Learning Theory, Machine Learning, Artificial Intelligence, Statistics, Optimization.

His recent articles reflect a diverse array of research interests and contributions to the field:

Medusa: Simple llm inference acceleration framework with multiple decoding heads

Reward-agnostic fine-tuning: Provable statistical benefits of hybrid reinforcement learning

Smoothing the landscape boosts the signal for sgd: Optimal sample complexity for learning single index models

Fine-tuning language models with just forward passes

Provable guarantees for nonlinear feature learning in three-layer neural networks

Implicit bias of gradient descent for logistic regression at the edge of stability

Offline minimax soft-q-learning under realizability and partial coverage

Understanding incremental learning of gradient descent: A fine-grained analysis of matrix sensing

Jason D. Lee Information

University

Position

Assistant Professor of Electrical Engineering

Citations(all)

15172

Citations(since 2020)

12952

Cited By

7038

hIndex(all)

57

hIndex(since 2020)

53

i10Index(all)

98

i10Index(since 2020)

96

Email

University Profile Page

Princeton University

Google Scholar

View Google Scholar Profile

Jason D. Lee Skills & Research Interests

Machine Learning Theory

Machine Learning

Artificial Intelligence

Statistics

Optimization

Top articles of Jason D. Lee

Title

Journal

Author(s)

Publication Date

Medusa: Simple llm inference acceleration framework with multiple decoding heads

arXiv preprint arXiv:2401.10774

Tianle Cai

Yuhong Li

Zhengyang Geng

Hongwu Peng

Jason D Lee

...

2024/1/19

Reward-agnostic fine-tuning: Provable statistical benefits of hybrid reinforcement learning

Advances in Neural Information Processing Systems

Gen Li

Wenhao Zhan

Jason D Lee

Yuejie Chi

Yuxin Chen

2024/2/13

Smoothing the landscape boosts the signal for sgd: Optimal sample complexity for learning single index models

Advances in Neural Information Processing Systems

Alex Damian

Eshaan Nichani

Rong Ge

Jason D Lee

2024/2/13

Fine-tuning language models with just forward passes

Advances in Neural Information Processing Systems

Sadhika Malladi

Tianyu Gao

Eshaan Nichani

Alex Damian

Jason D Lee

...

2024/2/13

Provable guarantees for nonlinear feature learning in three-layer neural networks

Advances in Neural Information Processing Systems

Eshaan Nichani

Alex Damian

Jason D Lee

2024/2/13

Implicit bias of gradient descent for logistic regression at the edge of stability

Advances in Neural Information Processing Systems

Jingfeng Wu

Vladimir Braverman

Jason D Lee

2024/2/13

Offline minimax soft-q-learning under realizability and partial coverage

Advances in Neural Information Processing Systems

Masatoshi Uehara

Nathan Kallus

Jason D Lee

Wen Sun

2024/2/13

Understanding incremental learning of gradient descent: A fine-grained analysis of matrix sensing

Jikai Jin

Zhiyuan Li

Kaifeng Lyu

Simon Shaolei Du

Jason D Lee

2023/7/3

Reconstructing training data from model gradient, provably

Zihan Wang

Jason Lee

Qi Lei

2023/4/11

Looped transformers as programmable computers

Angeliki Giannou

Shashank Rajput

Jy-yong Sohn

Kangwook Lee

Jason D Lee

...

2023/7/3

Optimal multi-distribution learning

arXiv preprint arXiv:2312.05134

Zihan Zhang

Wenhao Zhan

Yuxin Chen

Simon S Du

Jason D Lee

2023/12/8

Can We Find Nash Equilibria at a Linear Rate in Markov Games?

arXiv preprint arXiv:2303.03095

Zhuoqing Song

Jason D Lee

Zhuoran Yang

2023/3/3

Computationally efficient pac rl in pomdps with latent determinism and conditional embeddings

Masatoshi Uehara

Ayush Sekhari

Jason D Lee

Nathan Kallus

Wen Sun

2023/7/3

Rest: Retrieval-based speculative decoding

arXiv preprint arXiv:2311.08252

Zhenyu He

Zexuan Zhong

Tianle Cai

Jason D Lee

Di He

2023/11/14

Policy mirror descent for regularized reinforcement learning: A generalized framework with linear convergence

SIAM Journal on Optimization

Wenhao Zhan

Shicong Cen

Baihe Huang

Yuxin Chen

Jason D Lee

...

2023/6/30

Settling the sample complexity of online reinforcement learning

arXiv preprint arXiv:2307.13586

Zihan Zhang

Yuxin Chen

Jason D Lee

Simon S Du

2023/7/25

How to Query Human Feedback Efficiently in RL?

arXiv preprint arXiv:2305.18505

Wenhao Zhan

Masatoshi Uehara

Wen Sun

Jason D Lee

2023/5/29

Teaching arithmetic to small transformers

arXiv preprint arXiv:2307.03381

Nayoung Lee

Kartik Sreenivasan

Jason D Lee

Kangwook Lee

Dimitris Papailiopoulos

2023/7/7

Provable offline reinforcement learning with human feedback

arXiv preprint arXiv:2305.14816

Wenhao Zhan

Masatoshi Uehara

Nathan Kallus

Jason D Lee

Wen Sun

2023/5/24

Nearly minimax algorithms for linear bandits with shared representation

arXiv preprint arXiv:2203.15664

Jiaqi Yang

Qi Lei

Jason D Lee

Simon S Du

2022/3/29

See List of Professors in Jason D. Lee University(Princeton University)

Co-Authors

H-index: 203
Michael I. Jordan

Michael I. Jordan

University of California, Berkeley

H-index: 149
Trevor Hastie

Trevor Hastie

Stanford University

H-index: 90
Sham M Kakade

Sham M Kakade

University of Washington

H-index: 85
Benjamin Recht

Benjamin Recht

University of California, Berkeley

H-index: 73
Nathan Srebro

Nathan Srebro

Toyota Technological Institute

H-index: 63
Jonathan Taylor

Jonathan Taylor

Stanford University

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