Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training

20 November 2018

Papers citing "Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training"

11 / 11 papers shown

Title
Lifted Proximal Operator Machines Jia Li Cong Fang Zhouchen Lin ODL 29 36 0 05 Nov 2018
Lifted Neural Networks Armin Askari Geoffrey Negiar Rajiv Sambharya L. Ghaoui 86 37 0 03 May 2018
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training Tim Tsz-Kit Lau Jinshan Zeng Baoyuan Wu Yuan Yao ODL 36 33 0 24 Mar 2018
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks Ziming Zhang M. Brand 35 70 0 20 Nov 2017
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys Pratik Chaudhari A. Choromańska Stefano Soatto Yann LeCun Carlo Baldassi C. Borgs J. Chayes Levent Sagun R. Zecchina ODL 84 769 0 06 Nov 2016
Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention Yang Liu Chengjie Sun Mehdi Alizadeh Xiaolong Wang 45 274 0 30 May 2016
Training Neural Networks Without Gradients: A Scalable ADMM Approach Gavin Taylor R. Burmeister Zheng Xu Bharat Singh Ankit B. Patel Tom Goldstein ODL 42 274 0 06 May 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 328 43,154 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 850 149,474 0 22 Dec 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 106 1,380 0 10 Jun 2014
Distributed optimization of deeply nested systems M. A. Carreira-Perpiñán Weiran Wang 68 193 0 24 Dec 2012