Controllable Orthogonalization in Training DNNs

Controllable Orthogonalization in Training DNNs

2 April 2020

Papers citing "Controllable Orthogonalization in Training DNNs"

18 / 18 papers shown

Title
1-Lipschitz Neural Networks are more expressive with N-Activations Bernd Prach Christoph H. Lampert AAML FAtt 24 0 0 10 Nov 2023
Localization using Multi-Focal Spatial Attention for Masked Face Recognition Samrudhdhi B. Rangrej Hanbyel Cho H. Hong James J. Clark Dongmin Cho JungWoo Chang Junmo Kim CVBM 23 1 0 03 May 2023
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz Networks Bernd Prach Christoph H. Lampert 32 35 0 05 Aug 2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs Fanchen Bu D. Chang 17 6 0 12 May 2022
Compact Model Training by Low-Rank Projection with Energy Transfer K. Guo Zhenquan Lin Xiaofen Xing Fang Liu Xiangmin Xu 22 2 0 12 Apr 2022
projUNN: efficient method for training deep networks with unitary matrices B. Kiani Randall Balestriero Yann LeCun S. Lloyd 36 32 0 10 Mar 2022
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization Xiaojun Xu Jacky Y. Zhang Evelyn Ma Danny Son Oluwasanmi Koyejo Bo-wen Li 20 10 0 03 Feb 2022
Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values Zhenquan Lin K. Guo Xiaofen Xing Xiangmin Xu ODL 24 1 0 09 Oct 2021
Orthogonal Graph Neural Networks Kai Guo Kaixiong Zhou Xia Hu Yu Li Yi Chang Xin Wang 43 34 0 23 Sep 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks E. M. Achour Franccois Malgouyres Franck Mamalet 16 20 0 12 Aug 2021
Coordinate descent on the orthogonal group for recurrent neural network training E. Massart V. Abrol 29 10 0 30 Jul 2021
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks Kaixiong Zhou Xiao Shi Huang Daochen Zha Rui Chen Li Li Soo-Hyun Choi Xia Hu GNN AI4CE 22 114 0 06 Jul 2021
Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature Redundancy Mengzhu Wang Xiang Zhang L. Lan Wei Wang Huibin Tan Zhigang Luo AI4CE 37 1 0 28 Dec 2020
Transform Quantization for CNN (Convolutional Neural Network) Compression Sean I. Young Wang Zhe David S. Taubman B. Girod MQ 29 69 0 02 Sep 2020
Deep Isometric Learning for Visual Recognition Haozhi Qi Chong You X. Wang Yi-An Ma Jitendra Malik VLM 27 53 0 30 Jun 2020
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 220 348 0 14 Jun 2018
Optimization on Submanifolds of Convolution Kernels in CNNs Mete Ozay Takayuki Okatani 43 46 0 22 Oct 2016
Learning Unitary Operators with Help From u(n) Stephanie L. Hyland Gunnar Rätsch 89 41 0 17 Jul 2016