Papers citing 'Identifying and attacking the saddle point problem in high-dimensional non-convex optimization'

Title
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 298 250 0 29 Aug 2017
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study Peng Xu Farbod Roosta-Khorasani Michael W. Mahoney ODL 148 154 0 25 Aug 2017
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information Peng Xu Farbod Roosta-Khorasani Michael W. Mahoney 505 220 0 23 Aug 2017
On the Importance of Consistency in Training Deep Neural Networks Chengxi Ye Yezhou Yang Cornelia Fermuller Yiannis Aloimonos 69 12 0 02 Aug 2017
One-Shot Learning in Discriminative Neural Networks Jordan Burgess J. Lloyd Zoubin Ghahramani BDL VLM UQCV 167 11 0 18 Jul 2017
Machine Learning, Deepest Learning: Statistical Data Assimilation Problems H. Abarbanel P. Rozdeba S. Shirman PINN 136 78 0 05 Jul 2017
Optimization Beyond the Convolution: Generalizing Spatial Relations with End-to-End Metric Learning P. Jund Andreas Eitel N. Abdo Wolfram Burgard 3DPC 235 19 0 04 Jul 2017
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning Frank E. Curtis K. Scheinberg 175 48 0 30 Jun 2017
On the Optimization Landscape of Tensor Decompositions Rong Ge Tengyu Ma 170 95 0 18 Jun 2017
Stochastic Training of Neural Networks via Successive Convex Approximations Simone Scardapane Paolo Di Lorenzo 109 9 0 15 Jun 2017
Proximal BackpropagationInternational Conference on Learning Representations (ICLR), 2017 Thomas Frerix Thomas Möllenhoff Michael Möller Zorah Lähner 176 31 0 14 Jun 2017
A Well-Tempered Landscape for Non-convex Robust Subspace RecoveryJournal of machine learning research (JMLR), 2017 Tyler Maunu Teng Zhang Gilad Lerman 230 66 0 13 Jun 2017
Practical Gauss-Newton Optimisation for Deep LearningInternational Conference on Machine Learning (ICML), 2017 Aleksandar Botev H. Ritter David Barber ODL 306 243 0 12 Jun 2017
Recovery Guarantees for One-hidden-layer Neural NetworksInternational Conference on Machine Learning (ICML), 2017 Kai Zhong Zhao Song Prateek Jain Peter L. Bartlett Inderjit S. Dhillon MLT 345 344 0 10 Jun 2017
Global Convergence of the (1+1) Evolution StrategyEvolutionary Computation (Evol. Comput.), 2017 Tobias Glasmachers 122 13 0 09 Jun 2017
Learning Deep Representations for Scene Labeling with Semantic Context Guided Supervision Zhe Wang Jiaming Song Wanli Ouyang Xiaogang Wang SSL 98 2 0 08 Jun 2017
Are Saddles Good Enough for Deep Learning? Adepu Ravi Sankar V. Balasubramanian 158 6 0 07 Jun 2017
Spectral Norm Regularization for Improving the Generalizability of Deep Learning Yuichi Yoshida Takeru Miyato 209 374 0 31 May 2017
Convergence Analysis of Two-layer Neural Networks with ReLU Activation Yuanzhi Li Yang Yuan MLT 320 674 0 28 May 2017
Classification regions of deep neural networks Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard Stefano Soatto 130 52 0 26 May 2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks Elad Hoffer Itay Hubara Daniel Soudry ODL 411 844 0 24 May 2017
On the diffusion approximation of nonconvex stochastic gradient descent Junyang Qian C. J. Li Lei Li Jianguo Liu DiffM 190 24 0 22 May 2017
The Landscape of Deep Learning Algorithms Pan Zhou Jiashi Feng 181 25 0 19 May 2017
Sub-sampled Cubic Regularization for Non-convex Optimization Jonas Köhler Aurelien Lucchi 295 183 0 16 May 2017
Deep neural networks on graph signals for brain imaging analysis Yiluan Guo Hossein Nejati Ngai-Man Cheung GNN 157 28 0 13 May 2017
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting F. Bianchi E. Maiorino Michael C. Kampffmeyer A. Rizzi Robert Jenssen AI4TS 186 230 0 11 May 2017
The loss surface of deep and wide neural networks Quynh N. Nguyen Matthias Hein ODL 320 294 0 26 Apr 2017
Deep Relaxation: partial differential equations for optimizing deep neural networks Pratik Chaudhari Adam M. Oberman Stanley Osher Stefano Soatto G. Carlier 241 158 0 17 Apr 2017
Snapshot Ensembles: Train 1, get M for free Gao Huang Shouqing Yang Geoff Pleiss Zhuang Liu John E. Hopcroft Kilian Q. Weinberger OOD FedML UQCV 506 1,025 0 01 Apr 2017
Unifying the Stochastic Spectral Descent for Restricted Boltzmann Machines with Bernoulli or Gaussian Inputs Kai Fan 49 1 0 28 Mar 2017
Failures of Gradient-Based Deep Learning Shai Shalev-Shwartz Ohad Shamir Shaked Shammah ODL UQCV 274 219 0 23 Mar 2017
Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning M. S. Norouzzadeh Anh Totti Nguyen M. Kosmala A. Swanson Meredith Palmer C. Packer Jeff Clune HAI 296 48 0 16 Mar 2017
Sharp Minima Can Generalize For Deep Nets Laurent Dinh Razvan Pascanu Samy Bengio Yoshua Bengio ODL 369 827 0 15 Mar 2017
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks Nanyang Ye Zhanxing Zhu Rafał K. Mantiuk 218 21 0 13 Mar 2017
Large-scale image analysis using docker sandboxing B. Sengupta E. Vazquez Michele Sasdelli Y. Qian M. Peniak L. Netherton G. Delfino 68 4 0 07 Mar 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Sai Li ODL 358 888 0 02 Mar 2017
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis Yuandong Tian MLT 353 221 0 02 Mar 2017
On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation V. Ithapu Sathya Ravi Vikas Singh AI4CE 155 9 0 28 Feb 2017
Depth Creates No Bad Local Minima Haihao Lu Kenji Kawaguchi ODL FAtt 232 125 0 27 Feb 2017
On the Origin of Deep Learning Haohan Wang Bhiksha Raj MedIm 3DV VLM 310 234 0 24 Feb 2017
Strongly-Typed Agents are Guaranteed to Interact SafelyInternational Conference on Machine Learning (ICML), 2017 David Balduzzi 172 2 0 24 Feb 2017
Exponentially vanishing sub-optimal local minima in multilayer neural networksInternational Conference on Learning Representations (ICLR), 2017 Daniel Soudry Elad Hoffer 363 98 0 19 Feb 2017
Deep Stochastic Configuration Networks with Universal Approximation Property Dianhui Wang Ming Li BDL 113 6 0 18 Feb 2017
An Introduction to Deep Learning for the Physical LayerIEEE Transactions on Cognitive Communications and Networking (TCCN), 2017 Tim O'Shea J. Hoydis AI4CE 352 2,362 0 02 Feb 2017
Convergence Results for Neural Networks via ElectrodynamicsInformation Technology Convergence and Services (ITCS), 2017 Rina Panigrahy Sushant Sachdeva Qiuyi Zhang MLT MDE 230 22 0 01 Feb 2017
Reinforced stochastic gradient descent for deep neural network learning Haiping Huang Taro Toyoizumi ODL 137 1 0 27 Jan 2017
Maximum likelihood estimation of determinantal point processes Victor-Emmanuel Brunel Ankur Moitra Philippe Rigollet John C. Urschel 216 11 0 23 Jan 2017
Embedding Watermarks into Deep Neural NetworksInternational Conference on Multimedia Retrieval (ICMR), 2017 Yusuke Uchida Yuki Nagai S. Sakazawa Shiníchi Satoh 479 687 0 15 Jan 2017
Kernel Approximation Methods for Speech RecognitionJournal of machine learning research (JMLR), 2017 Avner May A. Garakani Zhiyun Lu Dong Guo Kuan Liu ... Michael Collins Daniel J. Hsu Brian Kingsbury M. Picheny Fei Sha 159 46 0 13 Jan 2017
An empirical analysis of the optimization of deep network loss surfaces Daniel Jiwoong Im Michael Tao K. Branson ODL 380 64 0 13 Dec 2016