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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
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 128 9 0 27 May 2022
Linear Connectivity Reveals Generalization Strategies Jeevesh Juneja Rachit Bansal Kyunghyun Cho João Sedoc Naomi Saphra 333 48 0 24 May 2022
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free Tianlong Chen Zhenyu Zhang Yihua Zhang Shiyu Chang Sijia Liu Zhangyang Wang AAML 80 25 0 24 May 2022
Interpolating Compressed Parameter Subspaces Siddhartha Datta N. Shadbolt 96 5 0 19 May 2022
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 258 138 0 19 May 2022
FuNNscope: Visual microscope for interactively exploring the loss landscape of fully connected neural networks Aleksandar Doknic Torsten Moller 102 2 0 09 Apr 2022
Improving Generalization in Federated Learning by Seeking Flat Minima Debora Caldarola Barbara Caputo Marco Ciccone FedML 101 112 0 22 Mar 2022
A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization With Non-isolated Local Minima Tae-Eon Ko Xiantao Li 72 2 0 21 Mar 2022
Low-Loss Subspace Compression for Clean Gains against Multi-Agent Backdoor Attacks Siddhartha Datta N. Shadbolt AAML 79 6 0 07 Mar 2022
Continual Learning Beyond a Single Model T. Doan Seyed Iman Mirzadeh Mehrdad Farajtabar CLL 92 16 0 20 Feb 2022
Geometric Regularization from Overparameterization Nicholas J. Teague 55 1 0 18 Feb 2022
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry Fabrizio Pittorino Antonio Ferraro Gabriele Perugini Christoph Feinauer Carlo Baldassi R. Zecchina 265 26 0 07 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 122 48 0 06 Feb 2022
When Do Flat Minima Optimizers Work? Jean Kaddour Linqing Liu Ricardo M. A. Silva Matt J. Kusner ODL 142 65 0 01 Feb 2022
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization G. Luca E. Silverstein 85 11 0 26 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 106 38 0 20 Jan 2022
Generalization in Supervised Learning Through Riemannian Contraction L. Kozachkov Patrick M. Wensing Jean-Jacques E. Slotine MLT 93 9 0 17 Jan 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 77 0 0 03 Jan 2022
LossPlot: A Better Way to Visualize Loss Landscapes Robert Bain M. Tokarev Harsh R Kothari Rahul Damineni 66 5 0 30 Nov 2021
Mode connectivity in the loss landscape of parameterized quantum circuits Kathleen E. Hamilton E. Lynn R. Pooser 72 3 0 09 Nov 2021
Exponential escape efficiency of SGD from sharp minima in non-stationary regime Hikaru Ibayashi Masaaki Imaizumi 97 4 0 07 Nov 2021
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks Aleksandr Shevchenko Vyacheslav Kungurtsev Marco Mondelli MLT 102 13 0 03 Nov 2021
Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector Guoliang Lin Hanlu Chu Hanjiang Lai MoMe CLL 92 50 0 15 Oct 2021
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework Zhiyuan Li Tianhao Wang Sanjeev Arora MLT 121 105 0 13 Oct 2021
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks R. Entezari Hanie Sedghi O. Saukh Behnam Neyshabur MoMe 106 238 0 12 Oct 2021
Tighter Sparse Approximation Bounds for ReLU Neural Networks Carles Domingo-Enrich Youssef Mroueh 143 4 0 07 Oct 2021
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective Luca Scimeca Seong Joon Oh Sanghyuk Chun Michael Poli Sangdoo Yun OOD 603 54 0 06 Oct 2021
Learning through atypical "phase transitions" in overparameterized neural networks Carlo Baldassi Clarissa Lauditi Enrico M. Malatesta R. Pacelli Gabriele Perugini R. Zecchina 101 27 0 01 Oct 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 94 19 0 16 Sep 2021
Supervising the Decoder of Variational Autoencoders to Improve Scientific Utility Liyun Tu Austin Talbot Neil Gallagher David Carlson DRL 76 3 0 09 Sep 2021
Using a one dimensional parabolic model of the full-batch loss to estimate learning rates during training Max Mutschler Kevin Laube A. Zell ODL 44 1 0 31 Aug 2021
Shift-Curvature, SGD, and Generalization Arwen V. Bradley C. Gomez-Uribe Manish Reddy Vuyyuru 62 3 0 21 Aug 2021
Taxonomizing local versus global structure in neural network loss landscapes Yaoqing Yang Liam Hodgkinson Ryan Theisen Joe Zou Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney 121 37 0 23 Jul 2021
Structured Directional Pruning via Perturbation Orthogonal Projection YinchuanLi XiaofengLiu YunfengShao QingWang YanhuiGeng 48 2 0 12 Jul 2021
What can linear interpolation of neural network loss landscapes tell us? Tiffany J. Vlaar Jonathan Frankle MoMe 76 28 0 30 Jun 2021
Revisiting Model Stitching to Compare Neural Representations Yamini Bansal Preetum Nakkiran Boaz Barak FedML 120 121 0 14 Jun 2021
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients Fan Mo Anastasia Borovykh Mohammad Malekzadeh Soteris Demetriou Deniz Gündüz Hamed Haddadi FedML 31 3 0 28 May 2021
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances Berfin cSimcsek François Ged Arthur Jacot Francesco Spadaro Clément Hongler W. Gerstner Johanni Brea AI4CE 87 102 0 25 May 2021
Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider A. Stakia T. Dorigo G. Banelli D. Bortoletto A. Casa ... G. Strong C. Tosciri J. Varela Pietro Vischia A. Weiler 38 3 0 16 May 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 81 389 0 29 Apr 2021
Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution Nemanja Rakićević Antoine Cully Petar Kormushev 54 34 0 27 Apr 2021
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes James Lucas Juhan Bae Michael Ruogu Zhang Stanislav Fort R. Zemel Roger C. Grosse MoMe 242 28 0 22 Apr 2021
MetricOpt: Learning to Optimize Black-Box Evaluation Metrics Chen Huang Shuangfei Zhai Pengsheng Guo J. Susskind 97 12 0 21 Apr 2021
Rehearsal revealed: The limits and merits of revisiting samples in continual learning Eli Verwimp Matthias De Lange Tinne Tuytelaars CLL 62 108 0 15 Apr 2021
Training Deep Neural Networks via Branch-and-Bound Yuanwei Wu Ziming Zhang Guanghui Wang ODL 57 0 0 05 Apr 2021
Empirically explaining SGD from a line search perspective Max Mutschler A. Zell ODL LRM 71 4 0 31 Mar 2021
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing Xiaohong Liu Zhihao Shi Zijun Wu Jun Chen 65 28 0 25 Mar 2021
Spurious Local Minima Are Common for Deep Neural Networks with Piecewise Linear Activations Bo Liu 53 7 0 25 Feb 2021
Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling Gregory W. Benton Wesley J. Maddox Sanae Lotfi A. Wilson UQCV 129 70 0 25 Feb 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization Tianyi Liu Yan Li S. Wei Enlu Zhou T. Zhao 65 13 0 24 Feb 2021