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Essentially No Barriers in Neural Network Energy Landscape

2 March 2018

Papers citing "Essentially No Barriers in Neural Network Energy Landscape"

50 / 295 papers shown

Title
Learning Neural Network Subspaces Mitchell Wortsman Maxwell Horton Carlos Guestrin Ali Farhadi Mohammad Rastegari UQCV 105 88 0 20 Feb 2021
When Are Solutions Connected in Deep Networks? Quynh N. Nguyen Pierre Bréchet Marco Mondelli 80 10 0 18 Feb 2021
Topological obstructions in neural networks learning S. Barannikov Daria Voronkova I. Trofimov Alexander Korotin Grigorii Sotnikov Evgeny Burnaev 39 6 0 31 Dec 2020
Recent advances in deep learning theory Fengxiang He Dacheng Tao AI4CE 132 51 0 20 Dec 2020
Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues Ricard Durall Avraam Chatzimichailidis P. Labus J. Keuper GAN 77 62 0 17 Dec 2020
Notes on Deep Learning Theory Eugene Golikov VLM AI4CE 25 2 0 10 Dec 2020
GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability Daniel Lengyel Janith C. Petangoda Isak Falk Kate Highnam Michalis Lazarou A. Kolbeinsson M. Deisenroth N. Jennings 73 5 0 14 Nov 2020
Numerical Exploration of Training Loss Level-Sets in Deep Neural Networks Naveed Tahir Garrett E. Katz 41 0 0 09 Nov 2020
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel Stanislav Fort Gintare Karolina Dziugaite Mansheej Paul Sepideh Kharaghani Daniel M. Roy Surya Ganguli 116 193 0 28 Oct 2020
Linear Mode Connectivity in Multitask and Continual Learning Seyed Iman Mirzadeh Mehrdad Farajtabar Dilan Görür Razvan Pascanu H. Ghasemzadeh CLL 88 147 0 09 Oct 2020
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win Utku Evci Yani Andrew Ioannou Cem Keskin Yann N. Dauphin 78 94 0 07 Oct 2020
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate Zhiyuan Li Kaifeng Lyu Sanjeev Arora 112 75 0 06 Oct 2020
Optimizing Mode Connectivity via Neuron Alignment N. Joseph Tatro Pin-Yu Chen Payel Das Igor Melnyk P. Sattigeri Rongjie Lai MoMe 328 82 0 05 Sep 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 101 262 0 04 Sep 2020
What is being transferred in transfer learning? Behnam Neyshabur Hanie Sedghi Chiyuan Zhang 155 531 0 26 Aug 2020
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry Yossi Arjevani M. Field 55 16 0 04 Aug 2020
Low-loss connection of weight vectors: distribution-based approaches Ivan Anokhin Dmitry Yarotsky 3DV 114 4 0 03 Aug 2020
Data-driven effective model shows a liquid-like deep learning Wenxuan Zou Haiping Huang 71 2 0 16 Jul 2020
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines A. Shilton Sunil Gupta Santu Rana Svetha Venkatesh 31 0 0 15 Jul 2020
The curious case of developmental BERTology: On sparsity, transfer learning, generalization and the brain Xin Wang 34 1 0 07 Jul 2020
The Global Landscape of Neural Networks: An Overview Ruoyu Sun Dawei Li Shiyu Liang Tian Ding R. Srikant 86 88 0 02 Jul 2020
Persistent Neurons Yimeng Min 31 0 0 02 Jul 2020
Learn Faster and Forget Slower via Fast and Stable Task Adaptation Farshid Varno Lucas May Petry Lisa Di-Jorio Stan Matwin CLL 64 2 0 02 Jul 2020
The Restricted Isometry of ReLU Networks: Generalization through Norm Concentration Alex Goessmann Gitta Kutyniok 30 3 0 01 Jul 2020
Dynamic of Stochastic Gradient Descent with State-Dependent Noise Qi Meng Shiqi Gong Wei Chen Zhi-Ming Ma Tie-Yan Liu 62 16 0 24 Jun 2020
Directional Pruning of Deep Neural Networks Shih-Kang Chao Zhanyu Wang Yue Xing Guang Cheng ODL 76 33 0 16 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 134 82 0 15 Jun 2020
Understanding Global Loss Landscape of One-hidden-layer ReLU Networks, Part 2: Experiments and Analysis Bo Liu 15 1 0 15 Jun 2020
Beyond Random Matrix Theory for Deep Networks Diego Granziol 123 16 0 13 Jun 2020
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape? Lifu Wang Bo Shen Ningrui Zhao Zhiyuan Zhang 59 16 0 10 Jun 2020
Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling Giulio Franzese Rosa Candela Dimitrios Milios Maurizio Filippone Pietro Michiardi 20 1 0 09 Jun 2020
Escaping Saddle Points Efficiently with Occupation-Time-Adapted Perturbations Xin Guo Jiequn Han Mahan Tajrobehkar Wenpin Tang 42 2 0 09 May 2020
The critical locus of overparameterized neural networks Y. Cooper UQCV 68 10 0 08 May 2020
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness Pu Zhao Pin-Yu Chen Payel Das Karthikeyan N. Ramamurthy Xue Lin AAML 158 192 0 30 Apr 2020
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima Enzo Tartaglione Andrea Bragagnolo Marco Grangetto 66 12 0 30 Apr 2020
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models Mengjie Zhao Tao R. Lin Fei Mi Martin Jaggi Hinrich Schütze 77 121 0 26 Apr 2020
Predicting the outputs of finite deep neural networks trained with noisy gradients Gadi Naveh Oded Ben-David H. Sompolinsky Zohar Ringel 116 23 0 02 Apr 2020
Towards Deep Learning Models Resistant to Large Perturbations Amirreza Shaeiri Rozhin Nobahari M. Rohban OOD AAML 81 12 0 30 Mar 2020
SuperNet -- An efficient method of neural networks ensembling Ludwik Bukowski W. Dzwinel 21 2 0 29 Mar 2020
Piecewise linear activations substantially shape the loss surfaces of neural networks Fengxiang He Bohan Wang Dacheng Tao ODL 91 30 0 27 Mar 2020
Interference and Generalization in Temporal Difference Learning Emmanuel Bengio Joelle Pineau Doina Precup 85 61 0 13 Mar 2020
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule Nikhil Iyer V. Thejas Nipun Kwatra Ramachandran Ramjee Muthian Sivathanu 89 29 0 09 Mar 2020
Some Geometrical and Topological Properties of DNNs' Decision Boundaries Bo Liu Mengya Shen AAML 78 3 0 07 Mar 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 190 658 0 20 Feb 2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function Lingkai Kong Molei Tao 57 23 0 14 Feb 2020
Understanding Global Loss Landscape of One-hidden-layer ReLU Networks, Part 1: Theory Bo Liu FAtt MLT 60 1 0 12 Feb 2020
A study of local optima for learning feature interactions using neural networks Yangzi Guo Adrian Barbu 115 1 0 11 Feb 2020
SQWA: Stochastic Quantized Weight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks Sungho Shin Yoonho Boo Wonyong Sung MQ 44 3 0 02 Feb 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks Aleksandr Shevchenko Marco Mondelli 196 38 0 20 Dec 2019
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 137 169 0 19 Dec 2019