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Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes

20 May 2016

Papers citing "Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes"

50 / 67 papers shown

Title
Entropy-Guided Sampling of Flat Modes in Discrete Spaces Pinaki Mohanty Riddhiman Bhattacharya Ruqi Zhang 572 0 0 05 May 2025
High-dimensional manifold of solutions in neural networks: insights from statistical physics Enrico M. Malatesta 194 4 0 20 Feb 2025
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens Vittorio Erba Emanuele Troiani Luca Biggio Antoine Maillard Lenka Zdeborová 253 2 0 24 Oct 2024
Exploring Loss Landscapes through the Lens of Spin Glass Theory Hao Liao Wei Zhang Zhanyi Huang Zexiao Long Mingyang Zhou Xiaoqun Wu Rui Mao Chi Ho Yeung 122 2 0 30 Jul 2024
Flat Posterior Does Matter For Bayesian Model Averaging Sungjun Lim Jeyoon Yeom Sooyon Kim Hoyoon Byun Jinho Kang Yohan Jung Jiyoung Jung Kyungwoo Song BDL AAML 241 0 0 21 Jun 2024
Strong convexity-guided hyper-parameter optimization for flatter losses Rahul Yedida Snehanshu Saha 132 0 0 07 Feb 2024
An effective theory of collective deep learning Lluís Arola-Fernández Lucas Lacasa FedML AI4CE 65 4 0 19 Oct 2023
Entropy-MCMC: Sampling from Flat Basins with Ease Bolian Li Ruqi Zhang 137 6 0 09 Oct 2023
On the different regimes of Stochastic Gradient Descent Antonio Sclocchi Matthieu Wyart 129 25 0 19 Sep 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 143 1 0 13 Sep 2023
The Copycat Perceptron: Smashing Barriers Through Collective Learning Giovanni Catania A. Decelle Beatriz Seoane FedML 72 2 0 07 Aug 2023
Eight challenges in developing theory of intelligence Haiping Huang 127 12 0 20 Jun 2023
Learning Capacity: A Measure of the Effective Dimensionality of a Model Daiwei Chen Wei-Di Chang Pratik Chaudhari 94 4 0 27 May 2023
Bayes Complexity of Learners vs Overfitting Grzegorz Gluch R. Urbanke UQCV BDL 62 1 0 13 Mar 2023
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 336 27 0 07 Feb 2022
Quantifying Relevance in Learning and Inference M. Marsili Y. Roudi 68 19 0 01 Feb 2022
Quantum Approximate Optimization Algorithm applied to the binary perceptron Pietro Torta G. Mbeng Carlo Baldassi R. Zecchina G. Santoro 68 8 0 19 Dec 2021
Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent Wei Zhang Mingrui Liu Yu Feng Xiaodong Cui Brian Kingsbury Yuhai Tu 69 4 0 02 Dec 2021
Equivalence between algorithmic instability and transition to replica symmetry breaking in perceptron learning systems Yang Zhao Junbin Qiu Mingshan Xie Haiping Huang 71 4 0 26 Nov 2021
Binary perceptron: efficient algorithms can find solutions in a rare well-connected cluster Emmanuel Abbe Shuangping Li Allan Sly MQ 119 38 0 04 Nov 2021
Deep learning via message passing algorithms based on belief propagation Carlo Lucibello Fabrizio Pittorino Gabriele Perugini R. Zecchina 156 15 0 27 Oct 2021
Learning through atypical "phase transitions" in overparameterized neural networks Carlo Baldassi Clarissa Lauditi Enrico M. Malatesta R. Pacelli Gabriele Perugini R. Zecchina 156 29 0 01 Oct 2021
Entropic alternatives to initialization Daniele Musso 110 1 0 16 Jul 2021
Unveiling the structure of wide flat minima in neural networks Carlo Baldassi Clarissa Lauditi Enrico M. Malatesta Gabriele Perugini R. Zecchina 186 39 0 02 Jul 2021
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging Anthony Sicilia Xingchen Zhao Anastasia Sosnovskikh Seong Jae Hwang BDL UQCV 116 4 0 12 Apr 2021
Proof of the Contiguity Conjecture and Lognormal Limit for the Symmetric Perceptron Emmanuel Abbe Shuangping Li Allan Sly 139 45 0 25 Feb 2021
SALR: Sharpness-aware Learning Rate Scheduler for Improved Generalization Xubo Yue Maher Nouiehed Raed Al Kontar ODL 83 4 0 10 Nov 2020
SGB: Stochastic Gradient Bound Method for Optimizing Partition Functions Junchang Wang A. Choromańska 69 0 0 03 Nov 2020
Some Remarks on Replicated Simulated Annealing Vicent Gripon Matthias Löwe Franck Vermet 85 2 0 30 Sep 2020
Partial local entropy and anisotropy in deep weight spaces Daniele Musso 103 3 0 17 Jul 2020
Entropic gradient descent algorithms and wide flat minima Fabrizio Pittorino Carlo Lucibello Christoph Feinauer Gabriele Perugini Carlo Baldassi Elizaveta Demyanenko R. Zecchina ODL MLT 217 35 0 14 Jun 2020
Beyond the storage capacity: data driven satisfiability transition P. Rotondo M. Pastore M. Gherardi 59 18 0 20 May 2020
How neural networks find generalizable solutions: Self-tuned annealing in deep learning Yu Feng Y. Tu MLT 77 9 0 06 Jan 2020
Clustering of solutions in the symmetric binary perceptron Carlo Baldassi R. D. Vecchia Carlo Lucibello R. Zecchina 122 23 0 15 Nov 2019
Mean-field inference methods for neural networks Marylou Gabrié AI4CE 156 33 0 03 Nov 2019
Natural representation of composite data with replicated autoencoders Matteo Negri D. Bergamini Carlo Baldassi R. Zecchina Christoph Feinauer SyDa 60 1 0 29 Sep 2019
Maximal Relevance and Optimal Learning Machines O. Duranthon M. Marsili R Xie 138 0 0 27 Sep 2019
Properties of the geometry of solutions and capacity of multi-layer neural networks with Rectified Linear Units activations Carlo Baldassi Enrico M. Malatesta R. Zecchina MLT 177 47 0 17 Jul 2019
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias Stéphane dÁscoli Levent Sagun Joan Bruna Giulio Biroli 110 37 0 16 Jun 2019
How to iron out rough landscapes and get optimal performances: Averaged Gradient Descent and its application to tensor PCA Giulio Biroli C. Cammarota F. Ricci-Tersenghi 115 28 0 29 May 2019
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension Yunfei Teng Wenbo Gao F. Chalus A. Choromańska Shiqian Ma Adrian Weller 172 14 0 24 May 2019
Shaping the learning landscape in neural networks around wide flat minima Carlo Baldassi Fabrizio Pittorino R. Zecchina MLT 141 86 0 20 May 2019
The loss surface of deep linear networks viewed through the algebraic geometry lens D. Mehta Tianran Chen Tingting Tang J. Hauenstein ODL 116 33 0 17 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 177 210 0 02 Oct 2018
Deep learning systems as complex networks Alberto Testolin Michele Piccolini S. Suweis AI4CE BDL GNN 49 29 0 28 Sep 2018
Optimization of neural networks via finite-value quantum fluctuations Masayuki Ohzeki Shuntaro Okada Masayoshi Terabe S. Taguchi 68 21 0 01 Jul 2018
Input and Weight Space Smoothing for Semi-supervised Learning Safa Cicek Stefano Soatto 75 6 0 23 May 2018
Glassy nature of the hard phase in inference problems F. Antenucci S. Franz Pierfrancesco Urbani Lenka Zdeborová 105 30 0 15 May 2018
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou Victor Veitch Morgane Austern Ryan P. Adams Peter Orbanz 151 219 0 16 Apr 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems Marco Baity-Jesi Levent Sagun Mario Geiger S. Spigler Gerard Ben Arous C. Cammarota Yann LeCun Matthieu Wyart Giulio Biroli AI4CE 162 117 0 19 Mar 2018