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Modelling the influence of data structure on learning in neural networks: the hidden manifold model

25 September 2019

Lenka Zdeborová

Papers citing "Modelling the influence of data structure on learning in neural networks: the hidden manifold model"

37 / 37 papers shown

Title
DNNs, Dataset Statistics, and Correlation Functions Robert W. Batterman James F. Woodward 8 0 0 18 Nov 2025
Geometry of Neural Reinforcement Learning in Continuous State and Action SpacesInternational Conference on Learning Representations (ICLR), 2025 Saket Tiwari Omer Gottesman George Konidaris 174 2 0 28 Jul 2025
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces Saket Tiwari Omer Gottesman George Konidaris 141 0 0 29 Dec 2022
Effects of Data Geometry in Early Deep LearningNeural Information Processing Systems (NeurIPS), 2022 Saket Tiwari George Konidaris 297 7 0 29 Dec 2022
On the Robustness of Bayesian Neural Networks to Adversarial AttacksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 Luca Bortolussi Ginevra Carbone Luca Laurenti A. Patané G. Sanguinetti Matthew Wicker AAML 223 14 0 13 Jul 2022
Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian dataAnnual Conference on Information Sciences and Systems (CISS), 2022 Hongkang Li Shuai Zhang Ming Wang MLT 183 10 0 07 Jul 2022
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape GeometryInternational Conference on Machine Learning (ICML), 2022 Fabrizio Pittorino Antonio Ferraro Gabriele Perugini Christoph Feinauer Carlo Baldassi R. Zecchina 468 28 0 07 Feb 2022
Quantifying Relevance in Learning and InferencePhysics reports (Phys. Rep.), 2022 M. Marsili Y. Roudi 128 20 0 01 Feb 2022
The emergence of a concept in shallow neural networksNeural Networks (NN), 2021 E. Agliari Francesco Alemanno Adriano Barra G. D. Marzo 141 49 0 01 Sep 2021
Deep Networks Provably Classify Data on CurvesNeural Information Processing Systems (NeurIPS), 2021 Tingran Wang Sam Buchanan D. Gilboa John N. Wright 214 9 0 29 Jul 2021
Slope and generalization properties of neural networks Anton Johansson Niklas Engsner Claes Strannegård P. Mostad OOD 74 0 0 03 Jul 2021
Probing transfer learning with a model of synthetic correlated datasets Federica Gerace Luca Saglietti Stefano Sarao Mannelli Andrew M. Saxe Lenka Zdeborová OOD 161 36 0 09 Jun 2021
On the interplay between data structure and loss function in classification problemsNeural Information Processing Systems (NeurIPS), 2021 Stéphane dÁscoli Marylou Gabrié Levent Sagun Giulio Biroli 224 17 0 09 Mar 2021
Learning curves of generic features maps for realistic datasets with a teacher-student modelNeural Information Processing Systems (NeurIPS), 2021 Bruno Loureiro Cédric Gerbelot Hugo Cui Sebastian Goldt Florent Krzakala M. Mézard Lenka Zdeborová 310 152 0 16 Feb 2021
On Data-Augmentation and Consistency-Based Semi-Supervised LearningInternational Conference on Learning Representations (ICLR), 2021 Atin Ghosh Alexandre Hoang Thiery 182 22 0 18 Jan 2021
Solvable Model for Inheriting the Regularization through Knowledge DistillationMathematical and Scientific Machine Learning (MSML), 2020 Luca Saglietti Lenka Zdeborová 265 22 0 01 Dec 2020
Toward Better Generalization Bounds with Locally Elastic StabilityInternational Conference on Machine Learning (ICML), 2020 Zhun Deng Hangfeng He Weijie J. Su 210 49 0 27 Oct 2020
What causes the test error? Going beyond bias-variance via ANOVAJournal of machine learning research (JMLR), 2020 Licong Lin Guang Cheng 252 35 0 11 Oct 2020
Deep Networks and the Multiple Manifold ProblemInternational Conference on Learning Representations (ICLR), 2020 Sam Buchanan D. Gilboa John N. Wright 417 41 0 25 Aug 2020
Universality of Linearized Message Passing for Phase Retrieval with Structured Sensing Matrices Rishabh Dudeja Milad Bakhshizadeh 351 13 0 24 Aug 2020
Geometric compression of invariant manifolds in neural nets J. Paccolat Leonardo Petrini Mario Geiger Kevin Tyloo Matthieu Wyart MLT 236 37 0 22 Jul 2020
Large scale analysis of generalization error in learning using margin based classification methodsJournal of Statistical Mechanics: Theory and Experiment (JSTAT), 2020 Hanwen Huang Qinglong Yang 132 9 0 16 Jul 2020
Hierarchical nucleation in deep neural networks Diego Doimo Aldo Glielmo A. Ansuini Alessandro Laio BDL AI4CE 163 35 0 07 Jul 2020
Is SGD a Bayesian sampler? Well, almost Chris Mingard Guillermo Valle Pérez Joar Skalse A. Louis BDL 224 61 0 26 Jun 2020
Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver Levent Sagun Çağlar Gülçehre Adriana Romero Negar Rostamzadeh Stefano Sarao Mannelli 3DV 108 0 0 25 Jun 2020
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani Thang Doan Masashi Sugiyama CLL 370 70 0 21 Jun 2020
How isotropic kernels perform on simple invariants J. Paccolat S. Spigler Matthieu Wyart 263 4 0 17 Jun 2020
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classificationNeural Information Processing Systems (NeurIPS), 2020 Francesca Mignacco Florent Krzakala Pierfrancesco Urbani Lenka Zdeborová MLT 284 73 0 10 Jun 2020
Triple descent and the two kinds of overfitting: Where & why do they appear? Stéphane dÁscoli Levent Sagun Giulio Biroli 210 84 0 05 Jun 2020
Optimal Learning with Excitatory and Inhibitory synapses Alessandro Ingrosso 68 5 0 25 May 2020
Fractional Deep Neural Network via Constrained Optimization Harbir Antil R. Khatri R. Löhner Deepanshu Verma 144 32 0 01 Apr 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy RegimeInternational Conference on Machine Learning (ICML), 2020 Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 367 158 0 02 Mar 2020
Generalisation error in learning with random features and the hidden manifold modelInternational Conference on Machine Learning (ICML), 2020 Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 255 179 0 21 Feb 2020
Robustness of Bayesian Neural Networks to Gradient-Based AttacksNeural Information Processing Systems (NeurIPS), 2020 Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 213 82 0 11 Feb 2020
Mean-field inference methods for neural networks Marylou Gabrié AI4CE 311 35 0 03 Nov 2019
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation Elisa Oostwal Michiel Straat Michael Biehl MLT 221 64 0 16 Oct 2019
The Local Elasticity of Neural NetworksInternational Conference on Learning Representations (ICLR), 2019 Hangfeng He Weijie J. Su 262 51 0 15 Oct 2019