On the interplay between data structure and loss function in
classification problems

On the interplay between data structure and loss function in classification problems

9 March 2021

Stéphane dÁscoli

Marylou Gabrié

Papers citing "On the interplay between data structure and loss function in classification problems"

15 / 15 papers shown

Title
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks Behrad Moniri Donghwan Lee Hamed Hassani Yan Sun MLT 55 21 0 11 Oct 2023
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 215 264 0 18 Apr 2021
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 46 61 0 03 Aug 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 60 188 0 24 Jun 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 21 170 0 12 Jun 2020
$On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression$ On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear Regression Denny Wu Ji Xu 47 122 0 10 Jun 2020
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent Zhenyu Liao Romain Couillet Michael W. Mahoney 36 88 0 09 Jun 2020
The role of regularization in classification of high-dimensional noisy Gaussian mixture Francesca Mignacco Florent Krzakala Yue M. Lu Lenka Zdeborová 6 89 0 26 Feb 2020
Generalisation error in learning with random features and the hidden manifold model Federica Gerace Bruno Loureiro Florent Krzakala M. Mézard Lenka Zdeborová 43 168 0 21 Feb 2020
Mean-field inference methods for neural networks Marylou Gabrié AI4CE 36 33 0 03 Nov 2019
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks Sanjeev Arora S. Du Zhiyuan Li Ruslan Salakhutdinov Ruosong Wang Dingli Yu AAML 27 162 0 03 Oct 2019
Modelling the influence of data structure on learning in neural networks: the hidden manifold model Sebastian Goldt M. Mézard Florent Krzakala Lenka Zdeborová BDL 44 51 0 25 Sep 2019
Asymptotic learning curves of kernel methods: empirical data v.s. Teacher-Student paradigm S. Spigler Mario Geiger Matthieu Wyart 30 38 0 26 May 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 61 737 0 19 Mar 2019
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models Jean Barbier Florent Krzakala N. Macris Léo Miolane Lenka Zdeborová 55 262 0 10 Aug 2017

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