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2011.07729
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Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View
Neural Information Processing Systems (NeurIPS), 2020
16 November 2020
Christos Thrampoulidis
Samet Oymak
Mahdi Soltanolkotabi
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Papers citing
"Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View"
27 / 27 papers shown
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When and How Unlabeled Data Provably Improve In-Context Learning
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Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm
Journal of Statistical Mechanics: Theory and Experiment (JSTAT), 2024
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Tomoyuki Obuchi
533
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29 Nov 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
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249
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Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets
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28 May 2024
One-Bit Quantization and Sparsification for Multiclass Linear Classification via Regularized Regression
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16 Feb 2024
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification
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13 Feb 2024
Regularized Linear Regression for Binary Classification
International Symposium on Information Theory (ISIT), 2023
D. Akhtiamov
Reza Ghane
Babak Hassibi
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03 Nov 2023
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
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Malik Tiomoko
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287
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20 Oct 2023
Noisy Interpolation Learning with Shallow Univariate ReLU Networks
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Gal Vardi
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343
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Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
Neural Information Processing Systems (NeurIPS), 2023
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Pierre C. Bellec
286
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28 May 2023
From Tempered to Benign Overfitting in ReLU Neural Networks
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326
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24 May 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Minh-Toan Nguyen
Romain Couillet
284
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03 Mar 2023
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization
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Spencer Frei
Gal Vardi
Peter L. Bartlett
Nathan Srebro
253
31
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02 Mar 2023
Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation
Luca Pesce
Florent Krzakala
Bruno Loureiro
Ludovic Stephan
291
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17 Feb 2023
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Neural Information Processing Systems (NeurIPS), 2022
Lijia Zhou
Frederic Koehler
Pragya Sur
Danica J. Sutherland
Nathan Srebro
394
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0
21 Oct 2022
SphereFed: Hyperspherical Federated Learning
European Conference on Computer Vision (ECCV), 2022
Xin Dong
Shanghang Zhang
Ang Li
H. T. Kung
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267
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19 Jul 2022
Generalization for multiclass classification with overparameterized linear models
Neural Information Processing Systems (NeurIPS), 2022
Vignesh Subramanian
Rahul Arya
A. Sahai
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259
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03 Jun 2022
A Modern Theory for High-dimensional Cox Regression Models
Xianyang Zhang
Huijuan Zhou
Hanxuan Ye
214
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03 Apr 2022
Learning curves for the multi-class teacher-student perceptron
Elisabetta Cornacchia
Francesca Mignacco
R. Veiga
Cédric Gerbelot
Bruno Loureiro
Lenka Zdeborová
387
21
0
22 Mar 2022
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Ali Bereyhi
Bruno Loureiro
Florent Krzakala
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445
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On the Regularization of Autoencoders
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Dario Garcia-Garcia
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292
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21 Oct 2021
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
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Ke Wang
Vidya Muthukumar
Christos Thrampoulidis
350
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0
21 Jun 2021
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions
Neural Information Processing Systems (NeurIPS), 2021
Bruno Loureiro
G. Sicuro
Cédric Gerbelot
Alessandro Pacco
Florent Krzakala
Lenka Zdeborová
325
69
0
07 Jun 2021
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation
Acta Numerica (AN), 2021
M. Belkin
295
219
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29 May 2021
Fine-grained Generalization Analysis of Vector-valued Learning
AAAI Conference on Artificial Intelligence (AAAI), 2021
Liang Wu
Antoine Ledent
Yunwen Lei
Matthias Kirchler
200
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29 Apr 2021
A Concentration of Measure Framework to study convex problems and other implicit formulation problems in machine learning
Cosme Louart
333
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19 Oct 2020
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