Learning Gaussian Mixtures with Generalised Linear Models: Precise
Asymptotics in High-dimensions

Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions

7 June 2021

Cédric Gerbelot

Alessandro Pacco

Florent Krzakala

Lenka Zdeborová

Papers citing "Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions"

14 / 14 papers shown

Title
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure Samet Demir Zafer Dogan MLT 36 0 0 02 Mar 2025
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model Kaito Takanami Takashi Takahashi Ayaka Sakata 40 1 0 27 Jan 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs Kasimir Tanner Matteo Vilucchio Bruno Loureiro Florent Krzakala AAML 63 0 0 31 Dec 2024
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm Xiaosi Gu Tomoyuki Obuchi 77 0 0 29 Nov 2024
When resampling/reweighting improves feature learning in imbalanced classification?: A toy-model study Tomoyuki Obuchi Toshiyuki Tanaka 64 0 0 09 Sep 2024
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets Khen Cohen Noam Levi Yaron Oz BDL 33 1 0 28 May 2024
IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency Linshan Hou Ruili Feng Zhongyun Hua Wei Luo Leo Yu Zhang Yiming Li AAML 48 19 0 16 May 2024
Spectral alignment of stochastic gradient descent for high-dimensional classification tasks Gerard Ben Arous Reza Gheissari Jiaoyang Huang Aukosh Jagannath 35 13 0 04 Oct 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models David X. Wu A. Sahai 29 2 0 23 Jun 2023
Least Squares Regression Can Exhibit Under-Parameterized Double Descent Xinyue Li Rishi Sonthalia 44 3 0 24 May 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture Minh-Toan Nguyen Romain Couillet 30 4 0 03 Mar 2023
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning Ali Bereyhi Bruno Loureiro Florent Krzakala R. Muller H. Schulz-Baldes 35 2 0 19 Jan 2022
The Lasso with general Gaussian designs with applications to hypothesis testing Michael Celentano Andrea Montanari Yuting Wei 42 63 0 27 Jul 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar Cengiz Pehlevan 149 201 0 07 Feb 2020