Training Neural Networks Without Gradients: A Scalable ADMM Approach

6 May 2016

Papers citing "Training Neural Networks Without Gradients: A Scalable ADMM Approach"

46 / 46 papers shown

Title
ADMM-Based Training for Spiking Neural Networks Giovanni Perin Cesare Bidini Riccardo Mazzieri M. Rossi 34 0 0 08 May 2025
Occlusion-Aware Contingency Safety-Critical Planning for Autonomous Vehicles Lei Zheng Rui Yang Minzhe Zheng Zengqi Peng Michael Yu Wang Jun Ma 48 1 0 10 Feb 2025
BADM: Batch ADMM for Deep Learning Ouya Wang Shenglong Zhou Geoffrey Ye Li ODL 50 1 0 30 Jun 2024
PRIEST: Projection Guided Sampling-Based Optimization For Autonomous Navigation Fatemeh Rastgar Houman Masnavi Basant Sharma A. Aabloo Jan Swevers Ashutosh Kumar Singh 36 4 0 15 Sep 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
Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons R. Høier D. Staudt Christopher Zach 31 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
Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization Ye-ling Shi Leijie Zhang Zehong Cao M. Tanveer Chin-Teng Lin 14 7 0 18 Sep 2022
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods Jintao Xu Chenglong Bao W. Xing 8 3 0 30 Aug 2022
Learning with Local Gradients at the Edge M. Lomnitz Z. Daniels David C. Zhang M. Piacentino 34 1 0 17 Aug 2022
Gradient Descent on Neurons and its Link to Approximate Second-Order Optimization Frederik Benzing ODL 43 23 0 28 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 27 34 0 20 Jan 2022
Training Recurrent Neural Networks by Sequential Least Squares and the Alternating Direction Method of Multipliers Alberto Bemporad 27 11 0 31 Dec 2021
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 41 9 0 17 Dec 2021
Target Propagation via Regularized Inversion Vincent Roulet Zaïd Harchaoui BDL AAML 27 4 0 02 Dec 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 72 69 0 09 Nov 2021
Multi-Modal Model Predictive Control through Batch Non-Holonomic Trajectory Optimization: Application to Highway Driving V. K. Adajania Aditya Sharma Anish Gupta Houman Masnavi M. Krishna A. K. Singh 68 26 0 21 Sep 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021
Stochastic Block-ADMM for Training Deep Networks Saeed Khorram Xiao Fu Mohamad H. Danesh Zhongang Qi Li Fuxin 34 3 0 01 May 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Differentiable Programming à la Moreau Vincent Roulet Zaïd Harchaoui 23 5 0 31 Dec 2020
Deep Convolutional Transform Learning -- Extended version Jyoti Maggu A. Majumdar Émilie Chouzenoux Giovanni Chierchia 16 5 0 02 Oct 2020
Learning and Optimization of Blackbox Combinatorial Solvers in Neural Networks T. J. Wilder 11 0 0 06 Jun 2020
Large-Scale Gradient-Free Deep Learning with Recursive Local Representation Alignment Alexander Ororbia A. Mali Daniel Kifer C. Lee Giles 23 2 0 10 Feb 2020
Fast Polynomial Kernel Classification for Massive Data Jinshan Zeng Minrun Wu Shao-Bo Lin Ding-Xuan Zhou TPM 16 5 0 24 Nov 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
Inertial nonconvex alternating minimizations for the image deblurring Tao Sun R. Barrio Marcos Rodríguez Hao Jiang 16 12 0 27 Jul 2019
Associated Learning: Decomposing End-to-end Backpropagation based on Auto-encoders and Target Propagation Yu-Wei Kao Hung-Hsuan Chen BDL 20 5 0 13 Jun 2019
Decoupled Greedy Learning of CNNs Eugene Belilovsky Michael Eickenberg Edouard Oyallon 8 114 0 23 Jan 2019
Differentially Private ADMM for Distributed Medical Machine Learning Jiahao Ding Xiaoqi Qin Wenjun Xu Yanmin Gong Zhu Han Miao Pan FedML 32 20 0 07 Jan 2019
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 21 40 0 19 Nov 2018
Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks Nikola B. Kovachki Andrew M. Stuart BDL 42 136 0 10 Aug 2018
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables A. Choromańska Benjamin Cowen Yara Rizk Ronny Luss Mattia Rigotti ... Brian Kingsbury Paolo Diachille V. Gurev Ravi Tejwani Djallel Bouneffouf 21 52 0 24 Jun 2018
Local Critic Training of Deep Neural Networks Hojung Lee Jong-Seok Lee 33 8 0 03 May 2018
Decoupled Parallel Backpropagation with Convergence Guarantee Zhouyuan Huo Bin Gu Qian Yang Heng-Chiao Huang 23 97 0 27 Apr 2018
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision Sathya Ravi Tuan Dinh Vishnu Suresh Lokhande Vikas Singh AI4CE 33 22 0 17 Mar 2018
Deep Component Analysis via Alternating Direction Neural Networks Calvin Murdock Ming-Fang Chang Simon Lucey BDL 27 20 0 16 Mar 2018
Global Convergence of Block Coordinate Descent in Deep Learning Jinshan Zeng Tim Tsz-Kit Lau Shaobo Lin Yuan Yao 22 77 0 01 Mar 2018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis Tal Ben-Nun Torsten Hoefler GNN 33 703 0 26 Feb 2018
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks Ziming Zhang M. Brand 26 70 0 20 Nov 2017
Block-Cyclic Stochastic Coordinate Descent for Deep Neural Networks Kensuke Nakamura Stefano Soatto Byung-Woo Hong BDL ODL 43 6 0 20 Nov 2017
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem A. Friesen Pedro M. Domingos 26 20 0 31 Oct 2017
Proximal Backpropagation Thomas Frerix Thomas Möllenhoff Michael Möller Daniel Cremers 23 31 0 14 Jun 2017
A Probabilistic Framework for Deep Learning Ankit B. Patel M. T. Nguyen Richard G. Baraniuk BDL 31 67 0 06 Dec 2016
Decoupled Neural Interfaces using Synthetic Gradients Max Jaderberg Wojciech M. Czarnecki Simon Osindero Oriol Vinyals Alex Graves David Silver Koray Kavukcuoglu 44 353 0 18 Aug 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 183 1,185 0 30 Nov 2014