Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation

9 February 2023

Papers citing "Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation"

7 / 7 papers shown

Title
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach Kaiyi Ji Lei Ying 16 7 0 04 Jan 2023
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms Mathieu Dagréou Pierre Ablin Samuel Vaiter Thomas Moreau 129 95 0 31 Jan 2022
Amortized Implicit Differentiation for Stochastic Bilevel Optimization Michael Arbel Julien Mairal 101 58 0 29 Nov 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 99 714 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,568 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 112 404 0 06 Mar 2017