Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks

20 November 2017

Papers citing "Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks"

41 / 41 papers shown

Title
A Primal-dual algorithm for image reconstruction with ICNNs Hok Shing Wong Matthias Joachim Ehrhardt Subhadip Mukherjee 26 1 0 16 Oct 2024
Towards training digitally-tied analog blocks via hybrid gradient computation Timothy Nest M. Ernoult 44 1 0 05 Sep 2024
Differentially Private Neural Network Training under Hidden State Assumption Ding Chen Chen Liu FedML 29 0 0 11 Jul 2024
Complexity of Block Coordinate Descent with Proximal Regularization and Applications to Wasserstein CP-dictionary Learning Dohyun Kwon Hanbaek Lyu 14 3 0 04 Jun 2023
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee Chenyang Li Jihoon Chung Mengnan Du Haimin Wang Xianlian Zhou Bohao Shen 33 1 0 13 Mar 2023
Offsite-Tuning: Transfer Learning without Full Model Guangxuan Xiao Ji Lin Song Han 35 67 0 09 Feb 2023
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons R. Høier D. Staudt Christopher Zach 26 11 0 02 Feb 2023
Deep Incubation: Training Large Models by Divide-and-Conquering Zanlin Ni Yulin Wang Jiangwei Yu Haojun Jiang Yu Cao Gao Huang VLM 18 11 0 08 Dec 2022
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods Jintao Xu Chenglong Bao W. Xing 8 3 0 30 Aug 2022
0/1 Deep Neural Networks via Block Coordinate Descent Hui Zhang Shenglong Zhou Geoffrey Ye Li N. Xiu 33 7 0 19 Jun 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 25 34 0 20 Jan 2022
Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent Guanhua Ye Hongzhi Yin Tong Chen Miao Xu Quoc Viet Hung Nguyen Jiangning Song 37 9 0 17 Dec 2021
Modeling Design and Control Problems Involving Neural Network Surrogates Dominic Yang Prasanna Balaprakash S. Leyffer 23 13 0 20 Nov 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 59 69 0 09 Nov 2021
Transformer-Encoder-GRU (T-E-GRU) for Chinese Sentiment Analysis on Chinese Comment Text Binlong Zhang Wei Zhou 11 17 0 01 Aug 2021
LocoProp: Enhancing BackProp via Local Loss Optimization Ehsan Amid Rohan Anil Manfred K. Warmuth ODL 13 19 0 11 Jun 2021
Bilevel Programs Meet Deep Learning: A Unifying View on Inference Learning Methods Christopher Zach FedML 11 5 0 15 May 2021
Stochastic Block-ADMM for Training Deep Networks Saeed Khorram Xiao Fu Mohamad H. Danesh Zhongang Qi Li Fuxin 29 3 0 01 May 2021
Training Deep Neural Networks via Branch-and-Bound Yuanwei Wu Ziming Zhang Guanghui Wang ODL 20 0 0 05 Apr 2021
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training Linbo Qiao Tao Sun H. Pan Dongsheng Li 11 3 0 30 Jan 2021
Learning DNN networks using un-rectifying ReLU with compressed sensing application W. Hwang Shih-Shuo Tung 6 2 0 18 Jan 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 20 3 0 09 Jan 2021
Lifted Regression/Reconstruction Networks R. Høier Christopher Zach 8 7 0 07 May 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey Zhenheng Tang S. Shi Wei Wang Bo-wen Li Xiaowen Chu 19 48 0 10 Mar 2020
Semi-Implicit Back Propagation Ren Liu Xiaoqun Zhang ODL 8 0 0 10 Feb 2020
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters Ziming Zhang Wenchi Ma Yuanwei Wu Guanghui Wang 32 10 0 05 Jan 2020
Effects of Depth, Width, and Initialization: A Convergence Analysis of Layer-wise Training for Deep Linear Neural Networks Yeonjong Shin 17 12 0 14 Oct 2019
Towards Learning Affine-Invariant Representations via Data-Efficient CNNs Xenju Xu Guanghui Wang Alan Sullivan Ziming Zhang 17 23 0 31 Aug 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
Contrastive Learning for Lifted Networks Christopher Zach V. Estellers SSL 17 12 0 07 May 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 13 10 0 18 Dec 2018
Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training Fangda Gu Armin Askari L. Ghaoui 8 39 0 20 Nov 2018
Lifted Proximal Operator Machines Jia Li♂ Cong Fang Zhouchen Lin ODL 9 36 0 05 Nov 2018
A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation Ramin Raziperchikolaei Harish S. Bhat 9 5 0 16 Oct 2018
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables A. Choromańska Benjamin Cowen Sadhana Kumaravel Ronny Luss Mattia Rigotti ... Brian Kingsbury Paolo Diachille V. Gurev Ravi Tejwani Djallel Bouneffouf 6 52 0 24 Jun 2018
A Unified Framework for Training Neural Networks H. Ghauch H. S. Ghadikolaei Carlo Fischione Mikael Skoglund AI4CE 11 0 0 23 May 2018
A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training Tim Tsz-Kit Lau Jinshan Zeng Baoyuan Wu Y. Yao ODL 17 33 0 24 Mar 2018
Global Convergence of Block Coordinate Descent in Deep Learning Jinshan Zeng Tim Tsz-Kit Lau Shaobo Lin Y. Yao 15 77 0 01 Mar 2018
Block-Cyclic Stochastic Coordinate Descent for Deep Neural Networks Kensuke Nakamura Stefano Soatto Byung-Woo Hong BDL ODL 27 6 0 20 Nov 2017
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning Ziming Zhang Yuanwei Wu Guanghui Wang ODL 28 28 0 19 Nov 2017
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 179 1,185 0 30 Nov 2014