Deep Learning Theory Review: An Optimal Control and Dynamical Systems
Perspective

Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective

28 August 2019

Evangelos A. Theodorou

Papers citing "Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective"

17 / 17 papers shown

Title
Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks S. Sunada T. Niiyama Kazutaka Kanno Rin Nogami André Röhm Takato Awano Atsushi Uchida AI4CE 78 1 0 26 Feb 2025
Data Selection via Optimal Control for Language Models Yuxian Gu Li Dong Hongning Wang Y. Hao Qingxiu Dong Furu Wei Minlie Huang AI4CE 58 5 0 09 Oct 2024
Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity Quincy Hershey Randy Paffenroth Harsh Nilesh Pathak Simon Tavener 71 1 0 01 Apr 2024
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares Anant Raj Melih Barsbey Mert Gurbuzbalaban Lingjiong Zhu Umut Simsekli 19 9 0 02 Jun 2022
Kullback-Leibler control for discrete-time nonlinear systems on continuous spaces Kaito Ito Kenji Kashima 19 6 0 24 Mar 2022
Optimal learning rate schedules in high-dimensional non-convex optimization problems Stéphane dÁscoli Maria Refinetti Giulio Biroli 23 7 0 09 Feb 2022
Physical deep learning based on optimal control of dynamical systems Genki Furuhata T. Niiyama S. Sunada PINN AI4CE 29 14 0 16 Dec 2020
Learn to Synchronize, Synchronize to Learn Pietro Verzelli Cesare Alippi L. Livi 19 26 0 06 Oct 2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks Guan-Horng Liu T. Chen Evangelos A. Theodorou 24 2 0 17 Jul 2020
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods Adam Stooke Joshua Achiam Pieter Abbeel 31 287 0 08 Jul 2020
A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm O. Romero Subhro Das Pin-Yu Chen S. Pequito 8 1 0 23 Jun 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 39 78 0 11 Mar 2020
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 21 16 0 25 Oct 2019
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 244 350 0 14 Jun 2018
First-order Methods Almost Always Avoid Saddle Points Jason D. Lee Ioannis Panageas Georgios Piliouras Max Simchowitz Michael I. Jordan Benjamin Recht ODL 95 83 0 20 Oct 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 463 11,715 0 09 Mar 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,896 0 15 Sep 2016