Seguir
Bin Hu
Título
Citado por
Citado por
Año
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
173*2021
Dissipativity Theory for Nesterov's Accelerated Method
B Hu, L Lessard
International Conference on Machine Learning (ICML), 1549-1557, 2017
1412017
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
882018
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
782023
Analysis of biased stochastic gradient descent using sequential semidefinite programs
B Hu, P Seiler, L Lessard
Mathematical Programming 187, 383-408, 2020
712020
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
682019
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
602020
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
57*2021
Control interpretations for first-order optimization methods
B Hu, L Lessard
2017 American Control Conference (ACC), 3114-3119, 2017
552017
A Unified Algebraic Perspective on Lipschitz Neural Networks
A Araujo, AJ Havens, B Delattre, A Allauzen, B Hu
International Conference on Learning Representations, 2023
512023
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
492016
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
462023
Robust convergence analysis of distributed optimization algorithms
A Sundararajan, B Hu, L Lessard
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
452017
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
442024
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
382017
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
332017
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
282018
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
242024
Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on Model-Free Control of Markovian Jump Systems
JP Jansch-Porto, B Hu, G Dullerud
Learning for Dynamics and Control, 947-957, 2020
222020
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20