Maxim Raginsky
University of Illinois at Urbana-Champaign
H-index: 35
North America-United States
Top articles of Maxim Raginsky
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
A unified framework for information-theoretic generalization bounds | Advances in Neural Information Processing Systems | Yifeng Chu Maxim Raginsky | 2024/2/13 |
Rademacher Complexity of Neural ODEs via Chen-Fliess Series | arXiv preprint arXiv:2401.16655 | Joshua Hanson Maxim Raginsky | 2024/1/30 |
Transformer-based models are not yet perfect at learning to emulate structural recursion | arXiv preprint arXiv:2401.12947 | Dylan Zhang Curt Tigges Zory Zhang Stella Biderman Maxim Raginsky | 2024/1/23 |
Some Remarks on Controllability of the Liouville Equation | arXiv preprint arXiv:2404.14683 | Maxim Raginsky | 2024/4/23 |
Revisiting Stochastic Realization Theory using Functional It\^ o Calculus | arXiv preprint arXiv:2402.10157 | Tanya Veeravalli Maxim Raginsky | 2024/2/15 |
Variational principles for mirror descent and mirror langevin dynamics | IEEE Control Systems Letters | Belinda Tzen Anant Raj Maxim Raginsky Francis Bach | 2023/5/8 |
Generalization bounds: Perspectives from information theory and PAC-Bayes | arXiv preprint arXiv:2309.04381 | Fredrik Hellström Giuseppe Durisi Benjamin Guedj Maxim Raginsky | 2023/9/8 |
Stochastic Differential Equations: A Systems-Theoretic Approach (DRAFT) | Maxim Raginsky | 2023/5/1 | |
Partially observed discrete-time risk-sensitive mean field games | Dynamic Games and Applications | Naci Saldi Tamer Başar Maxim Raginsky | 2023/9 |
A Chain Rule for the Expected Suprema of Bernoulli Processes | arXiv preprint arXiv:2304.14474 | Yifeng Chu Maxim Raginsky | 2023/4/27 |
Majorizing Measures, Codes, and Information | Yifeng Chu Maxim Raginsky | 2023/6/25 | |
Nonlinear controllability and function representation by neural stochastic differential equations | Tanya Veeravalli Maxim Raginsky | 2023/6/6 | |
A Constructive Approach to Function Realization by Neural Stochastic Differential Equations | Tanya Veeravalli Maxim Raginsky | 2023/12/13 | |
Can Transformers Learn to Solve Problems Recursively? | arXiv preprint arXiv:2305.14699 | Shizhuo Dylan Zhang Curt Tigges Stella Biderman Maxim Raginsky Talia Ringer | 2023/5/24 |
Biological Autonomy | Maxim Raginsky | 2023/12 | |
Conference on Learning Theory 2022: Preface | Po-Ling Loh Maxim Raginsky | 2022/9/1 | |
Minimum excess risk in Bayesian learning | IEEE Transactions on Information Theory | Aolin Xu Maxim Raginsky | 2022/5/23 |
Input-to-state stable neural ordinary differential equations with applications to transient modeling of circuits | Alan Yang Jie Xiong Maxim Raginsky Elyse Rosenbaum | 2022/5/11 | |
Robustness to incorrect models and data-driven learning in average-cost optimal stochastic control | Automatica | Ali Devran Kara Maxim Raginsky Serdar Yüksel | 2022/5/1 |
Fitting an immersed submanifold to data via Sussmann’s orbit theorem | Joshua Hanson Maxim Raginsky | 2022/12/6 |
Co-Authors
