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Bin Hu
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Policy Optimization for Linear Control with Robustness Guarantee: Implicit Regularization and Global Convergence
K Zhang, B Hu, T Başar
SIAM Journal on Control and Optimization 59 (6), 4081-4109, 2021
176*2021
Dissipativity Theory for Nesterov's Accelerated Method
B Hu, L Lessard
International Conference on Machine Learning (ICML), 1549-1557, 2017
1402017
A robust accelerated optimization algorithm for strongly convex functions
S Cyrus, B Hu, B Van Scoy, L Lessard
2018 Annual American Control Conference (ACC), 1376-1381, 2018
902018
Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies
B Hu, K Zhang, N Li, M Mesbahi, M Fazel, T Başar
Annual Review of Control, Robotics, and Autonomous Systems 6, 123-158, 2023
872023
Characterizing the exact behaviors of temporal difference learning algorithms using Markov jump linear system theory
B Hu, U Syed
Advances in Neural Information Processing Systems, 8479-8490, 2019
712019
Cold-attack: Jailbreaking llms with stealthiness and controllability
X Guo, F Yu, H Zhang, L Qin, B Hu
Forty-first International Conference on Machine Learning, 2024
642024
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
K Zhang, X Zhang, B Hu, T Basar
Advances in Neural Information Processing Systems 34, 2949-2964, 2021
592021
Analysis of biased stochastic gradient descent using sequential semidefinite programs
B Hu, P Seiler, L Lessard
Mathematical Programming 187, 383-408, 2020
582020
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems
K Zhang, B Hu, T Basar
Advances in Neural Information Processing Systems 33, 22056-22068, 2020
582020
Control interpretations for first-order optimization methods
B Hu, L Lessard
2017 American Control Conference (ACC), 3114-3119, 2017
562017
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
H Xue, A Araujo, B Hu, Y Chen
Thirty-seventh Conference on Neural Information Processing Systems, 2023
532023
A Unified Algebraic Perspective on Lipschitz Neural Networks
A Araujo, AJ Havens, B Delattre, A Allauzen, B Hu
International Conference on Learning Representations, 2023
532023
Exponential decay rate conditions for uncertain linear systems using integral quadratic constraints
B Hu, P Seiler
IEEE Transactions on Automatic Control 61 (11), 3631-3637, 2016
472016
Robust convergence analysis of distributed optimization algorithms
A Sundararajan, B Hu, L Lessard
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
452017
Convergence guarantees of policy optimization methods for markovian jump linear systems
JP Jansch-Porto, B Hu, GE Dullerud
2020 American Control Conference (ACC), 2882-2887, 2020
422020
A unified analysis of stochastic optimization methods using jump system theory and quadratic constraints
B Hu, P Seiler, A Rantzer
Conference on Learning Theory (COLT), 1157-1189, 2017
392017
Robustness analysis of uncertain discrete‐time systems with dissipation inequalities and integral quadratic constraints
B Hu, MJ Lacerda, P Seiler
International Journal of Robust and Nonlinear Control 27 (11), 1940-1962, 2017
342017
Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra
D Kevian, U Syed, X Guo, A Havens, G Dullerud, P Seiler, L Qin, B Hu
arXiv preprint arXiv:2404.03647, 2024
282024
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
B Hu, S Wright, L Lessard
International Conference on Machine Learning (ICML), 2038-2047, 2018
262018
Learning the Kalman filter with fine-grained sample complexity
X Zhang, B Hu, T Başar
2023 American Control Conference (ACC), 4549-4554, 2023
232023
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Artikler 1–20