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2002.11544
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The role of regularization in classification of high-dimensional noisy Gaussian mixture
26 February 2020
Francesca Mignacco
Florent Krzakala
Yue M. Lu
Lenka Zdeborová
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Papers citing
"The role of regularization in classification of high-dimensional noisy Gaussian mixture"
50 / 58 papers shown
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Statistical Inference in Classification of High-dimensional Gaussian Mixture
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Asymptotics of feature learning in two-layer networks after one gradient-step
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Freya Behrens
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Lenka Zdeborová
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Asymptotic generalization error of a single-layer graph convolutional network
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Luca Saglietti
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Regularized Linear Regression for Binary Classification
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Babak Hassibi
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Least Squares Regression Can Exhibit Under-Parameterized Double Descent
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65
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Universality laws for Gaussian mixtures in generalized linear models
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Florent Krzakala
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102
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Florent Krzakala
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Homophily modulates double descent generalization in graph convolution networks
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Jiaye Teng
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Gaussian Universality of Perceptrons with Random Labels
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107
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I. Reichardt
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Roger Guimerà
98
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Ashkan Panahi
Ayça Özçelikkale
Devdatt Dubhash
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Learning curves for the multi-class teacher-student perceptron
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R. Veiga
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91
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81
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Optimal regularizations for data generation with probabilistic graphical models
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Simona Cocco
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Hanshu Yan
Vincent Y. F. Tan
109
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Vidya Muthukumar
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Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions
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Lenka Zdeborová
76
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Minimum complexity interpolation in random features models
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Theodor Misiakiewicz
Andrea Montanari
59
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The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression
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Daniel LeJeune
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Levent Sagun
Giulio Biroli
100
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Label-Imbalanced and Group-Sensitive Classification under Overparameterization
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Orestis Paraskevas
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129
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Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
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Lenka Zdeborová
92
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61
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Phase Transitions in Transfer Learning for High-Dimensional Perceptrons
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Solvable Model for Inheriting the Regularization through Knowledge Distillation
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53
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Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting and Regularization
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101
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73
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