Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?

22 October 2018

Papers citing "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?"

7 / 107 papers shown

Title
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group Mario Lezcano Casado David Martínez-Rubio 50 200 0 24 Jan 2019
Learning Compositional Representations for Few-Shot Recognition P. Tokmakov Yu-Xiong Wang M. Hebert OCL 74 126 0 21 Dec 2018
Information Geometry of Orthogonal Initializations and Training Piotr A. Sokól Il-Su Park AI4CE 125 17 0 09 Oct 2018
Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions Jinhyeok Jang Hyunjoong Cho Jaehong Kim Jaeyeon Lee Seungjoon Yang 20 2 0 11 Sep 2018
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation Anastasis Kratsios Cody B. Hyndman OOD 69 17 0 31 Aug 2018
Learning Simple Thresholded Features with Sparse Support Recovery Hongyu Xu Zhangyang Wang Haichuan Yang Ding Liu Ji Liu 79 32 0 16 Apr 2018
Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding Dong Liu Ke Sun Zhangyang Wang Runsheng Liu Zhengjun Zha 86 12 0 28 Feb 2018