Bin Hu

Bin Hu

University of Illinois at Urbana-Champaign

H-index: 17

North America-United States

About Bin Hu

Bin Hu, With an exceptional h-index of 17 and a recent h-index of 17 (since 2020), a distinguished researcher at University of Illinois at Urbana-Champaign, specializes in the field of Machine Learning, Optimization, Control Theory.

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

Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability

On the scalability and memory efficiency of semidefinite programs for Lipschitz constant estimation of neural networks

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models

Complexity of Derivative-Free Policy Optimization for Structured Control

Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability

Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies

Bin Hu Information

University

Position

___

Citations(all)

1031

Citations(since 2020)

919

Cited By

410

hIndex(all)

17

hIndex(since 2020)

17

i10Index(all)

26

i10Index(since 2020)

23

Email

University Profile Page

Google Scholar

Bin Hu Skills & Research Interests

Machine Learning

Optimization

Control Theory

Top articles of Bin Hu

Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra

arXiv preprint arXiv:2404.03647

2024/4/4

COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability

arXiv preprint arXiv:2402.08679

2024/2/13

On the scalability and memory efficiency of semidefinite programs for Lipschitz constant estimation of neural networks

2023/10/13

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations

arXiv preprint arXiv:2401.14033

2024/1/25

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models

Advances in Neural Information Processing Systems

2024/2/13

Complexity of Derivative-Free Policy Optimization for Structured Control

Advances in Neural Information Processing Systems

2024/2/13

Xingang Guo
Xingang Guo

H-Index: 3

Bin Hu
Bin Hu

H-Index: 11

Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability

Thirty-seventh Conference on Neural Information Processing Systems

2023/11/2

Bin Hu
Bin Hu

H-Index: 11

Yongxin Chen
Yongxin Chen

H-Index: 1

Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies

2023/5/3

Bounds for the Tracking Error and Dynamic Regret of Inexact Online Optimization Methods: A General Analysis via Sequential Semidefinite Programs

arXiv preprint arXiv:2303.00937

2023/3/2

Learning the Kalman filter with fine-grained sample complexity

arXiv preprint arXiv:2301.12624

2023/1/30

Bin Hu
Bin Hu

H-Index: 11

A Unified Algebraic Perspective on Lipschitz Neural Networks

arXiv preprint arXiv:2303.03169

2023/3/6

Aaron Havens
Aaron Havens

H-Index: 2

Bin Hu
Bin Hu

H-Index: 11

Global Convergence of Direct Policy Search for State-Feedback Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential

Advances in Neural Information Processing Systems

2022/12/6

Xingang Guo
Xingang Guo

H-Index: 3

Bin Hu
Bin Hu

H-Index: 11

Revisiting PGD Attacks for Stability Analysis of High-Dimensional Nonlinear Systems and Perception-Based Control

IEEE Control Systems Letters

2022/7/4

Aaron Havens
Aaron Havens

H-Index: 2

Bin Hu
Bin Hu

H-Index: 11

Connectivity of the Feasible and Sublevel Sets of Dynamic Output Feedback Control with Robustness Constraints

IEEE Control Systems Letters

2022/7/4

Bin Hu
Bin Hu

H-Index: 11

Yang Zheng
Yang Zheng

H-Index: 10

Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Out

2022/6/28

Model-free μ synthesis via adversarial reinforcement learning

2022/6/8

Aaron Havens
Aaron Havens

H-Index: 2

Bin Hu
Bin Hu

H-Index: 11

Convex Programs and Lyapunov Functions for Reinforcement Learning: A Unified Perspective on the Analysis of Value-Based Methods

2022/6/8

Xingang Guo
Xingang Guo

H-Index: 3

Bin Hu
Bin Hu

H-Index: 11

Policy Optimization for Markovian Jump Linear Quadratic Control: Gradient Method and Global Convergence

IEEE Transactions on Automatic Control

2022/5/20

Exact Formulas for Finite-Time Estimation Errors of Decentralized Temporal Difference Learning with Linear Function Approximation

arXiv preprint arXiv:2204.09801

2022/4/20

Xingang Guo
Xingang Guo

H-Index: 3

Bin Hu
Bin Hu

H-Index: 11

Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity

Advances in Neural Information Processing Systems

2021/12/6

Kaiqing Zhang
Kaiqing Zhang

H-Index: 14

Bin Hu
Bin Hu

H-Index: 11

See List of Professors in Bin Hu University(University of Illinois at Urbana-Champaign)

Co-Authors

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