Generalization for multiclass classification with overparameterized linear models

3 June 2022

Papers citing "Generalization for multiclass classification with overparameterized linear models"

45 / 45 papers shown

Title
Provable Weak-to-Strong Generalization via Benign Overfitting David X. Wu A. Sahai 137 10 0 06 Oct 2024
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 72 3 0 23 Jun 2023
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 88 72 0 06 Sep 2021
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation Ke Wang Vidya Muthukumar Christos Thrampoulidis 64 49 0 21 Jun 2021
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation M. Belkin 53 186 0 29 May 2021
Deep learning: a statistical viewpoint Peter L. Bartlett Andrea Montanari Alexander Rakhlin 70 278 0 16 Mar 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization Ganesh Ramachandra Kini Orestis Paraskevas Samet Oymak Christos Thrampoulidis 90 96 0 02 Mar 2021
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View Christos Thrampoulidis Samet Oymak Mahdi Soltanolkotabi 65 43 0 16 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 120 688 0 06 Nov 2020
Benign overfitting in ridge regression Alexander Tsigler Peter L. Bartlett 75 167 0 29 Sep 2020
On the proliferation of support vectors in high dimensions Daniel J. Hsu Vidya Muthukumar Ji Xu 74 45 0 22 Sep 2020
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions Hossein Taheri Ramtin Pedarsani Christos Thrampoulidis 66 28 0 16 Jun 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 48 172 0 12 Jun 2020
Asymptotics of Ridge (less) Regression under General Source Condition Dominic Richards Jaouad Mourtada Lorenzo Rosasco 73 73 0 11 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 72 123 0 10 Jun 2020
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 94 151 0 16 May 2020
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime Niladri S. Chatterji Philip M. Long 54 109 0 25 Apr 2020
Sharp Asymptotics and Optimal Performance for Inference in Binary Models Hossein Taheri Ramtin Pedarsani Christos Thrampoulidis 69 25 0 17 Feb 2020
Analytic Study of Double Descent in Binary Classification: The Impact of Loss Ganesh Ramachandra Kini Christos Thrampoulidis 66 52 0 30 Jan 2020
More Data Can Hurt for Linear Regression: Sample-wise Double Descent Preetum Nakkiran 56 68 0 16 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 85 148 0 13 Nov 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 101 639 0 14 Aug 2019
Sampled Softmax with Random Fourier Features A. S. Rawat Jiecao Chen Felix X. Yu A. Suresh Sanjiv Kumar 75 55 0 24 Jul 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 88 778 0 26 Jun 2019
The Impact of Regularization on High-dimensional Logistic Regression Fariborz Salehi Ehsan Abbasi B. Hassibi 104 103 0 10 Jun 2019
Understanding overfitting peaks in generalization error: Analytical risk curves for $l_2$ and $l_1$ penalized interpolation P. Mitra 68 50 0 09 Jun 2019
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression Koby Bibas Yaniv Fogel M. Feder 41 34 0 12 May 2019
Harmless interpolation of noisy data in regression Vidya Muthukumar Kailas Vodrahalli Vignesh Subramanian A. Sahai 84 202 0 21 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 212 746 0 19 Mar 2019
Two models of double descent for weak features M. Belkin Daniel J. Hsu Ji Xu 106 375 0 18 Mar 2019
Visualising Basins of Attraction for the Cross-Entropy and the Squared Error Neural Network Loss Functions Anna Sergeevna Bosman A. Engelbrecht Mardé Helbig 59 77 0 08 Jan 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 244 1,655 0 28 Dec 2018
The jamming transition as a paradigm to understand the loss landscape of deep neural networks Mario Geiger S. Spigler Stéphane dÁscoli Levent Sagun Marco Baity-Jesi Giulio Biroli Matthieu Wyart 51 143 0 25 Sep 2018
Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization D. Kobak Jonathan Lomond Benoit Sanchez 60 89 0 28 May 2018
Convergence of Gradient Descent on Separable Data Mor Shpigel Nacson Jason D. Lee Suriya Gunasekar Pedro H. P. Savarese Nathan Srebro Daniel Soudry 76 169 0 05 Mar 2018
Characterizing Implicit Bias in Terms of Optimization Geometry Suriya Gunasekar Jason D. Lee Daniel Soudry Nathan Srebro AI4CE 73 411 0 22 Feb 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 72 420 0 05 Feb 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 163 923 0 27 Oct 2017
Squared Earth Mover's Distance-based Loss for Training Deep Neural Networks L. Hou Chen-Ping Yu Dimitris Samaras 114 152 0 17 Nov 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 351 4,635 0 10 Nov 2016
Multiclass Classification Calibration Functions Bernardo Avila-Pires Csaba Szepesvári 142 28 0 20 Sep 2016
Structured Prediction Theory Based on Factor Graph Complexity Corinna Cortes M. Mohri Vitaly Kuznetsov Scott Yang OOD 54 55 0 20 May 2016
A vector-contraction inequality for Rademacher complexities Andreas Maurer 77 261 0 01 May 2016
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms Yunwen Lei Ürün Dogan Alexander Binder Marius Kloft 56 57 0 14 Jun 2015
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning Behnam Neyshabur Ryota Tomioka Nathan Srebro AI4CE 99 662 0 20 Dec 2014