ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1709.06079
  4. Cited By
Orthogonal Weight Normalization: Solution to Optimization over Multiple
  Dependent Stiefel Manifolds in Deep Neural Networks

Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks

16 September 2017
Lei Huang
Xianglong Liu
B. Lang
Adams Wei Yu
Yongliang Wang
Bo Li
    ODL
ArXivPDFHTML

Papers citing "Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks"

32 / 32 papers shown
Title
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities
Rahul Parhi
Michael Unser
39
5
0
05 Oct 2023
Decentralized Riemannian Conjugate Gradient Method on the Stiefel
  Manifold
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Jun Chen
Haishan Ye
Mengmeng Wang
Tianxin Huang
Guangwen Dai
Ivor W.Tsang
Y. Liu
21
10
0
21 Aug 2023
Group Orthogonalization Regularization For Vision Models Adaptation and
  Robustness
Group Orthogonalization Regularization For Vision Models Adaptation and Robustness
Yoav Kurtz
Noga Bar
Raja Giryes
24
0
0
16 Jun 2023
Auto-Encoding Goodness of Fit
Auto-Encoding Goodness of Fit
A. Palmer
Zhiyi Chi
Derek Aguiar
J. Bi
38
1
0
12 Oct 2022
AdaWCT: Adaptive Whitening and Coloring Style Injection
AdaWCT: Adaptive Whitening and Coloring Style Injection
Antoine Dufour
Yohan Poirier-Ginter
Alexandre Lessard
Ryan Smith
Michael Lockyer
Jean-François Lalonde
26
1
0
01 Aug 2022
Entangled Residual Mappings
Entangled Residual Mappings
Mathias Lechner
Ramin Hasani
Z. Babaiee
Radu Grosu
Daniela Rus
T. Henzinger
Sepp Hochreiter
6
4
0
02 Jun 2022
Feedback Gradient Descent: Efficient and Stable Optimization with
  Orthogonality for DNNs
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs
Fanchen Bu
D. Chang
17
6
0
12 May 2022
Riemannian Hamiltonian methods for min-max optimization on manifolds
Riemannian Hamiltonian methods for min-max optimization on manifolds
Andi Han
Bamdev Mishra
Pratik Jawanpuria
Pawan Kumar
Junbin Gao
30
16
0
25 Apr 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Sebastian Neumayer
Alexis Goujon
Pakshal Bohra
M. Unser
24
15
0
13 Apr 2022
The Principle of Diversity: Training Stronger Vision Transformers Calls
  for Reducing All Levels of Redundancy
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy
Tianlong Chen
Zhenyu (Allen) Zhang
Yu Cheng
Ahmed Hassan Awadallah
Zhangyang Wang
ViT
35
37
0
12 Mar 2022
Learning Connectivity with Graph Convolutional Networks for
  Skeleton-based Action Recognition
Learning Connectivity with Graph Convolutional Networks for Skeleton-based Action Recognition
H. Sahbi
GNN
23
27
0
06 Dec 2021
Orthogonal Graph Neural Networks
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
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
Coordinate descent on the orthogonal group for recurrent neural network training
E. Massart
V. Abrol
29
10
0
30 Jul 2021
R-Drop: Regularized Dropout for Neural Networks
R-Drop: Regularized Dropout for Neural Networks
Xiaobo Liang
Lijun Wu
Juntao Li
Yue Wang
Qi Meng
Tao Qin
Wei Chen
M. Zhang
Tie-Yan Liu
41
424
0
28 Jun 2021
Improving Molecular Graph Neural Network Explainability with
  Orthonormalization and Induced Sparsity
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson
Djork-Arné Clevert
F. Montanari
27
26
0
11 May 2021
Skeleton-based Hand-Gesture Recognition with Lightweight Graph
  Convolutional Networks
Skeleton-based Hand-Gesture Recognition with Lightweight Graph Convolutional Networks
H. Sahbi
3DH
GNN
18
3
0
09 Apr 2021
Delving into Variance Transmission and Normalization: Shift of Average
  Gradient Makes the Network Collapse
Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse
YuXiang Liu
Jidong Ge
Chuanyi Li
Jie Gui
15
2
0
22 Mar 2021
Learning with Hyperspherical Uniformity
Learning with Hyperspherical Uniformity
Weiyang Liu
Rongmei Lin
Zhen Liu
Li Xiong
Bernhard Schölkopf
Adrian Weller
28
35
0
02 Mar 2021
Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature
  Redundancy
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
Continual Learning in Low-rank Orthogonal Subspaces
Continual Learning in Low-rank Orthogonal Subspaces
Arslan Chaudhry
Naeemullah Khan
P. Dokania
Philip H. S. Torr
CLL
33
113
0
22 Oct 2020
Deep Isometric Learning for Visual Recognition
Deep Isometric Learning for Visual Recognition
Haozhi Qi
Chong You
X. Wang
Yi-An Ma
Jitendra Malik
VLM
24
53
0
30 Jun 2020
Concept Whitening for Interpretable Image Recognition
Concept Whitening for Interpretable Image Recognition
Zhi Chen
Yijie Bei
Cynthia Rudin
FAtt
25
313
0
05 Feb 2020
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley
  Transform
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform
Jun Li
Fuxin Li
S. Todorovic
16
99
0
04 Feb 2020
Orthogonal Wasserstein GANs
Orthogonal Wasserstein GANs
J. Müller
Reinhard Klein
Michael Weinmann
40
9
0
29 Nov 2019
On Generalization Bounds of a Family of Recurrent Neural Networks
On Generalization Bounds of a Family of Recurrent Neural Networks
Minshuo Chen
Xingguo Li
T. Zhao
11
70
0
28 Oct 2019
Attentive Normalization
Attentive Normalization
Xilai Li
Wei Sun
Tianfu Wu
OOD
ViT
25
31
0
04 Aug 2019
ABD-Net: Attentive but Diverse Person Re-Identification
ABD-Net: Attentive but Diverse Person Re-Identification
Tianlong Chen
Shaojin Ding
Jingyi Xie
Ye Yuan
Wuyang Chen
Yang Yang
Zhou Ren
Zhangyang Wang
27
479
0
03 Aug 2019
Deep Asymmetric Networks with a Set of Node-wise Variant Activation
  Functions
Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions
Jinhyeok Jang
Hyunjoong Cho
Jaehong Kim
Jaeyeon Lee
Seungjoon Yang
15
2
0
11 Sep 2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets,
  and Beyond
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond
Xingguo Li
Junwei Lu
Zhaoran Wang
Jarvis D. Haupt
T. Zhao
25
78
0
13 Jun 2018
geomstats: a Python Package for Riemannian Geometry in Machine Learning
geomstats: a Python Package for Riemannian Geometry in Machine Learning
Nina Miolane
Johan Mathe
Claire Donnat
Mikael Jorda
Xavier Pennec
AI4CE
28
123
0
21 May 2018
Optimization on Submanifolds of Convolution Kernels in CNNs
Optimization on Submanifolds of Convolution Kernels in CNNs
Mete Ozay
Takayuki Okatani
43
46
0
22 Oct 2016
1