Exploiting Linear Structure Within Convolutional Networks for Efficient
Evaluation

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

2 April 2014

Emily L. Denton

Wojciech Zaremba

Joan Bruna

Papers citing "Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation"

14 / 14 papers shown

Title
Singular Value Scaling: Efficient Generative Model Compression via Pruned Weights Refinement H. Kim Jaejun Yoo 83 0 0 23 Dec 2024
Task Singular Vectors: Reducing Task Interference in Model Merging Antonio Andrea Gargiulo Donato Crisostomi Maria Sofia Bucarelli Simone Scardapane Fabrizio Silvestri Emanuele Rodolà MoMe 119 14 0 26 Nov 2024
Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods Akira Ito Masanori Yamada Atsutoshi Kumagai MoMe 83 5 0 06 Feb 2024
Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network Anh-Huy Phan Konstantin Sobolev Konstantin Sozykin Dmitry Ermilov Julia Gusak P. Tichavský Valeriy Glukhov Ivan Oseledets A. Cichocki BDL 44 129 0 12 Aug 2020
Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment Nenad Markuš Ivan Gogić Igor S. Pandzic Jörgen Ahlberg CVBM 35 1 0 27 Feb 2017
Deep Learning with Low Precision by Half-wave Gaussian Quantization Zhaowei Cai Xiaodong He Jian Sun Nuno Vasconcelos MQ 107 504 0 03 Feb 2017
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets Manuel Amthor E. Rodner Joachim Denzler 51 17 0 10 Oct 2016
Speeding up Convolutional Neural Networks with Low Rank Expansions Max Jaderberg Andrea Vedaldi Andrew Zisserman 123 1,458 0 15 May 2014
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks P. Sermanet David Eigen Xiang Zhang Michaël Mathieu Rob Fergus Yann LeCun ObjD 120 4,999 0 21 Dec 2013
Fast Training of Convolutional Networks through FFTs Michaël Mathieu Mikael Henaff Yann LeCun 95 607 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 289 15,825 0 12 Nov 2013
Predicting Parameters in Deep Learning Misha Denil B. Shakibi Laurent Dinh MarcÁurelio Ranzato Nando de Freitas OOD 132 1,314 0 03 Jun 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 371 7,650 0 03 Jul 2012
Building high-level features using large scale unsupervised learning Quoc V. Le MarcÁurelio Ranzato R. Monga M. Devin Kai Chen G. Corrado J. Dean A. Ng SSL OffRL CVBM 79 2,268 0 29 Dec 2011