DropAll: Generalization of Two Convolutional Neural Network Regularization Methods Xavier Fraz˜ao and Lu´ıs A. Alexandre Dept. of Informatics, Univ. Beira Interior and Instituto de Telecomunica¸co ˜es ?

Source URL: www.di.ubi.pt

Neural networks Training neural networks - regularization P MACHINE LEARNING

Source URL: dl.dropboxusercontent.com

Regularization from L1 by convolution 1 Introduction

Source URL: michel.talagrand.net

Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization H. Brendan McMahan Google, Inc.

Source URL: jmlr.org

Regularization of Neural Networks using DropConnect Li Wan Matthew Zeiler

Source URL: cs.nyu.edu

An Efficient ADMM Algorithm for Multidimensional Anisotropic Total Variation Regularization Problems Sen Yang1,2 , Jie Wang1,2 , Wei Fan3 , Xiatian Zhang3 , Peter Wonka2 , Jieping Ye1,2 1 Center for Evolutionary Medicin

Source URL: peterwonka.net

Journal de la Société Française de Statistique Vol. 155 NoComparing Model Selection and Regularization Approaches to Variable Selection in Model-Based Clustering

Source URL: www.stat.washington.edu

A concave regularization technique for sparse mixture models Martin Larsson School of Operations Research and Information Engineering Cornell University

Source URL: people.math.ethz.ch

REGULARIZATION OF CONTEXT-DEPENDENT DEEP NEURAL NETWORKS WITH CONTEXT-INDEPENDENT MULTI-TASK TRAINING Peter Bell and Steve Renals Centre for Speech Technology Research, University of Edinburgh, Edinburgh EH8 9AB, UK ABST

Source URL: www.cstr.inf.ed.ac.uk

227 Documenta Math. Two-Variable Zeta Functions and Regularized Products

Source URL: www.math.uiuc.edu

• Mathematical analysis
• Mathematics
• Analysis
• Theta function
• Complex analysis
• Zeta function regularization
• Local zeta-function
• Riemann zeta function