A Bregman Learning Framework for Sparse Neural Networks

10 May 2021

Papers citing "A Bregman Learning Framework for Sparse Neural Networks"

6 / 6 papers shown

Title
Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow T. J. Heeringa Tim Roith Christoph Brune Martin Burger 26 0 0 05 Dec 2023
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee Chenyang Li Jihoon Chung Mengnan Du Haimin Wang Xianlian Zhou Bohao Shen 33 1 0 13 Mar 2023
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 37 3 0 09 Nov 2022
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data L. Ho Nicholas Richardson Giang Tran 20 3 0 24 Aug 2021
How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang Ziyang Wu Jerry Chee Christopher De Sa Madeleine Udell 18 2 0 17 Jun 2021
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 153 685 0 31 Jan 2021