Gradient is All You Need?

16 June 2023

Papers citing "Gradient is All You Need?"

6 / 6 papers shown

Title
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization J. Carrillo Nicolas García Trillos Sixu Li Yuhua Zhu FedML 29 17 0 04 May 2023
Leveraging Memory Effects and Gradient Information in Consensus-Based Optimization: On Global Convergence in Mean-Field Law Konstantin Riedl 24 14 0 22 Nov 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach Grant M. Rotskoff Eric Vanden-Eijnden 59 118 0 02 May 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,199 0 16 Aug 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 179 1,185 0 30 Nov 2014