Achieving Linear Speedup in Non-IID Federated Bilevel Learning

Achieving Linear Speedup in Non-IID Federated Bilevel Learning

10 February 2023

Papers citing "Achieving Linear Speedup in Non-IID Federated Bilevel Learning"

10 / 10 papers shown

Title
Fully First-Order Methods for Decentralized Bilevel Optimization Xiaoyu Wang Xuxing Chen Shiqian Ma Tong Zhang 36 0 0 25 Oct 2024
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation Davoud Ataee Tarzanagh Mingchen Li Pranay Sharma Samet Oymak 24 0 0 02 Jun 2023
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach Kaiyi Ji Lei Ying 19 7 0 04 Jan 2023
A Penalty-Based Method for Communication-Efficient Decentralized Bilevel Programming Parvin Nazari Ahmad Mousavi Davoud Ataee Tarzanagh George Michailidis 19 4 0 08 Nov 2022
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 99 715 0 13 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 281 11,677 0 09 Mar 2017
Forward and Reverse Gradient-Based Hyperparameter Optimization Luca Franceschi Michele Donini P. Frasconi Massimiliano Pontil 115 405 0 06 Mar 2017