A Critical Review of Information Bottleneck Theory and its Applications to Deep Learning

7 May 2021

Papers citing "A Critical Review of Information Bottleneck Theory and its Applications to Deep Learning"

4 / 4 papers shown

Title
Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning Thanh-Dung Le R. Noumeir J. Rambaud Guillaume Sans P. Jouvet 30 7 0 26 Sep 2022
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 275 2,888 0 15 Sep 2016
Benefits of depth in neural networks Matus Telgarsky 128 602 0 14 Feb 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 177 1,185 0 30 Nov 2014