Guarantees for Tuning the Step Size using a Learning-to-Learn Approach

30 June 2020

Papers citing "Guarantees for Tuning the Step Size using a Learning-to-Learn Approach"

9 / 9 papers shown

Title
From Learning to Optimize to Learning Optimization Algorithms Camille Castera Peter Ochs 65 1 0 28 May 2024
A Nonstochastic Control Approach to Optimization Xinyi Chen Elad Hazan 47 5 0 19 Jan 2023
Learning-Rate-Free Learning by D-Adaptation Aaron Defazio Konstantin Mishchenko 30 77 0 18 Jan 2023
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 43 78 0 08 Jun 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split Samet Oymak Mingchen Li Mahdi Soltanolkotabi AI4CE OOD 36 13 0 29 Apr 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 43 225 0 23 Mar 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 371 11,700 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 133 409 0 06 Mar 2017
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 571 0 08 Dec 2012