Practical recommendations for gradient-based training of deep architectures

24 June 2012

Papers citing "Practical recommendations for gradient-based training of deep architectures"

13 / 13 papers shown

Title
Understanding the Functional Roles of Modelling Components in Spiking Neural Networks Huifeng Yin Hanle Zheng Jiayi Mao Siyuan Ding Xing Liu M. Xu Yifan Hu Jing Pei Lei Deng 95 1 0 28 Jan 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 125 3 0 28 Jan 2025
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis Weronika Ormaniec Felix Dangel Sidak Pal Singh 85 7 0 14 Oct 2024
Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin Ahmed Khaled Yuanhao Wang Aaron Defazio Robert Mansel Gower 68 9 0 06 Mar 2024
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 54 1 0 13 Sep 2023
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions Aaron Mishkin Arda Sahiner Mert Pilanci OffRL 97 30 0 02 Feb 2022
Learning Internal Representations (COLT 1995) Jonathan Baxter SSL AI4CE 80 400 0 13 Nov 2019
Implicit Density Estimation by Local Moment Matching to Sample from Auto-Encoders Yoshua Bengio Guillaume Alain Salah Rifai 39 12 0 30 Jun 2012
No More Pesky Learning Rates Tom Schaul Sixin Zhang Yann LeCun 89 477 0 06 Jun 2012
A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets Nicolas Le Roux Mark Schmidt Francis R. Bach ODL 53 103 0 28 Feb 2012
Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery Ian Goodfellow Aaron Courville Yoshua Bengio 42 61 0 16 Jan 2012
Natural Language Processing (almost) from Scratch R. Collobert Jason Weston Léon Bottou Michael Karlen Koray Kavukcuoglu Pavel P. Kuksa 128 7,711 0 02 Mar 2011
From Machine Learning to Machine Reasoning Léon Bottou LRM ReLM NAI 74 284 0 09 Feb 2011