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On the interplay of network structure and gradient convergence in deep learning

17 November 2015

Papers citing "On the interplay of network structure and gradient convergence in deep learning"

23 / 23 papers shown

Title
Network Morphism Tao Wei Changhu Wang Y. Rui Chen Chen 95 177 0 05 Mar 2016
Why are deep nets reversible: A simple theory, with implications for training Sanjeev Arora Yingyu Liang Tengyu Ma 87 54 0 18 Nov 2015
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas Haohan Wang Bhiksha Raj AI4TS 71 34 0 16 Oct 2015
Train faster, generalize better: Stability of stochastic gradient descent Moritz Hardt Benjamin Recht Y. Singer 120 1,243 0 03 Sep 2015
Constrained Convolutional Neural Networks for Weakly Supervised Segmentation Deepak Pathak Philipp Krahenbuhl Trevor Darrell SSeg 109 614 0 11 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 194 1,894 0 20 May 2015
A Probabilistic Theory of Deep Learning Ankit B. Patel M. T. Nguyen Richard G. Baraniuk BDL OOD UQCV 89 89 0 02 Apr 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 469 43,357 0 11 Feb 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 198 706 0 30 Dec 2014
FitNets: Hints for Thin Deep Nets Adriana Romero Nicolas Ballas Samira Ebrahimi Kahou Antoine Chassang C. Gatta Yoshua Bengio FedML 332 3,906 0 19 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 238 8,363 0 06 Nov 2014
On the Computational Efficiency of Training Neural Networks Roi Livni Shai Shalev-Shwartz Ohad Shamir 156 480 0 05 Oct 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 499 43,717 0 17 Sep 2014
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 450 20,611 0 10 Sep 2014
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization Yann N. Dauphin Razvan Pascanu Çağlar Gülçehre Kyunghyun Cho Surya Ganguli Yoshua Bengio ODL 134 1,394 0 10 Jun 2014
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 134 12,272 0 19 Dec 2013
Provable Bounds for Learning Some Deep Representations Sanjeev Arora Aditya Bhaskara Rong Ge Tengyu Ma BDL 109 335 0 23 Oct 2013
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 124 1,562 0 22 Sep 2013
Dropout Training as Adaptive Regularization Stefan Wager Sida I. Wang Percy Liang 133 600 0 04 Jul 2013
Maxout Networks Ian Goodfellow David Warde-Farley M. Berk Mirza Aaron Courville Yoshua Bengio OOD 280 2,179 0 18 Feb 2013
Deep Learning for Detecting Robotic Grasps Ian Lenz Honglak Lee Ashutosh Saxena 122 1,648 0 16 Jan 2013
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 296 12,467 0 24 Jun 2012
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 197 2,203 0 24 Jun 2012