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Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting

IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019

8 July 2019

Marc Lelarge

Léo Miolane

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Papers citing "Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting"

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Title
When and How Unlabeled Data Provably Improve In-Context Learning Yingcong Li Xiangyu Chang Muti Kara Xiaofeng Liu Amit K. Roy-Chowdhury Samet Oymak 128 1 0 18 Jun 2025
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model Kaito Takanami Takashi Takahashi Ayaka Sakata 278 2 0 27 Jan 2025
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional NetworksInternational Conference on Machine Learning (ICML), 2024 Hai-Xiao Wang Zhichao Wang 206 1 0 18 Dec 2024
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing AlgorithmJournal of Statistical Mechanics: Theory and Experiment (JSTAT), 2024 Xiaosi Gu Tomoyuki Obuchi 254 0 0 29 Nov 2024
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training Anchit Jain Rozhin Nobahari A. Baratin Stefano Sarao Mannelli 168 5 0 28 May 2024
Asymptotic Bayes risk of semi-supervised learning with uncertain labeling Victor Leger Romain Couillet 110 0 0 26 Mar 2024
Universal Lower Bounds and Optimal Rates: Achieving Minimax Clustering Error in Sub-Exponential Mixture Models Maximilien Dreveton Alperen Gozeten Matthias Grossglauser Patrick Thiran 212 4 0 23 Feb 2024
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption Vasilii Feofanov Malik Tiomoko Aladin Virmaux 124 8 0 20 Oct 2023
Classification of Heavy-tailed Features in High Dimensions: a Superstatistical ApproachNeural Information Processing Systems (NeurIPS), 2023 Urte Adomaityte G. Sicuro P. Vivo 135 11 0 06 Apr 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixtureInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Minh-Toan Nguyen Romain Couillet 104 4 0 03 Mar 2023
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine LearningIEEE Transactions on Quantum Engineering (IEEE Trans. Quantum Eng.), 2022 Massimiliano Incudini Michele Grossi Antonio Mandarino S. Vallecorsa Alessandra Di Pierro David Windridge 162 13 0 22 Dec 2022
Gaussian Universality of Perceptrons with Random LabelsPhysical Review E (Phys. Rev. E), 2022 Federica Gerace Florent Krzakala Bruno Loureiro Ludovic Stephan Lenka Zdeborová 197 26 0 26 May 2022
Bayesian Inference with Nonlinear Generative Models: Comments on Secure LearningIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022 Ali Bereyhi Bruno Loureiro Florent Krzakala R. Muller H. Schulz-Baldes 156 2 0 19 Jan 2022
PCA-based Multi Task Learning: a Random Matrix ApproachInternational Conference on Machine Learning (ICML), 2021 Malik Tiomoko Romain Couillet Frédéric Pascal 116 6 0 01 Nov 2021
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeedInternational Conference on Machine Learning (ICML), 2021 Maria Refinetti Sebastian Goldt Florent Krzakala Lenka Zdeborová 159 77 0 23 Feb 2021
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic ViewNeural Information Processing Systems (NeurIPS), 2020 Christos Thrampoulidis Samet Oymak Mahdi Soltanolkotabi 124 45 0 16 Nov 2020
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learningNeural Information Processing Systems (NeurIPS), 2020 Vivien A. Cabannes Loucas Pillaud-Vivien Francis R. Bach Alessandro Rudi 207 20 0 09 Sep 2020
Large Dimensional Analysis and Improvement of Multi Task Learning Malik Tiomoko Ali Romain Couillet Hafiz Tiomoko 73 8 0 03 Sep 2020
Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training Samet Oymak Talha Cihad Gulcu 129 20 0 19 Jun 2020
Entropic gradient descent algorithms and wide flat minimaInternational Conference on Learning Representations (ICLR), 2020 Fabrizio Pittorino Carlo Lucibello Christoph Feinauer Gabriele Perugini Carlo Baldassi Elizaveta Demyanenko R. Zecchina ODL MLT 257 35 0 14 Jun 2020
Consistent Semi-Supervised Graph Regularization for High Dimensional DataJournal of machine learning research (JMLR), 2020 Xiaoyi Mai Romain Couillet 51 16 0 13 Jun 2020
The role of regularization in classification of high-dimensional noisy Gaussian mixtureInternational Conference on Machine Learning (ICML), 2020 Francesca Mignacco Florent Krzakala Yue M. Lu Lenka Zdeborová 110 95 0 26 Feb 2020