Randomly Initialized One-Layer Neural Networks Make Data Linearly Separable

24 May 2022

Papers citing "Randomly Initialized One-Layer Neural Networks Make Data Linearly Separable"

9 / 9 papers shown

Title
On the Approximation Power of Two-Layer Networks of Random ReLUs Daniel J. Hsu Clayton Sanford Rocco A. Servedio Emmanouil-Vasileios Vlatakis-Gkaragkounis 48 25 0 03 Feb 2021
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 216 653 0 03 Aug 2018
Identity Matters in Deep Learning Moritz Hardt Tengyu Ma OOD 81 398 0 14 Nov 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 334 4,625 0 10 Nov 2016
Near-Optimal Bounds for Binary Embeddings of Arbitrary Sets Samet Oymak Ben Recht 33 33 0 14 Dec 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 309 18,609 0 06 Feb 2015
Deep Learning Face Representation by Joint Identification-Verification Yi Sun Xiaogang Wang Xiaoou Tang CVBM 222 2,247 0 18 Jun 2014
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 240 16,348 0 30 Apr 2014
Compressive classification and the rare eclipse problem Afonso S. Bandeira D. Mixon Benjamin Recht 49 33 0 11 Apr 2014