Universality of empirical risk minimization

17 February 2022

Papers citing "Universality of empirical risk minimization"

17 / 17 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 34 0 0 02 Mar 2025
Analysis of High-dimensional Gaussian Labeled-unlabeled Mixture Model via Message-passing Algorithm Xiaosi Gu Tomoyuki Obuchi 74 0 0 29 Nov 2024
Classifying Overlapping Gaussian Mixtures in High Dimensions: From Optimal Classifiers to Neural Nets Khen Cohen Noam Levi Yaron Oz BDL 31 1 0 28 May 2024
Asymptotic theory of in-context learning by linear attention Yue M. Lu Mary I. Letey Jacob A. Zavatone-Veth Anindita Maiti Cengiz Pehlevan 29 10 0 20 May 2024
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks Behrad Moniri Donghwan Lee Hamed Hassani Yan Sun MLT 40 19 0 11 Oct 2023
Exact threshold for approximate ellipsoid fitting of random points Antoine Maillard Afonso S. Bandeira 29 2 0 09 Oct 2023
Fitting an ellipsoid to random points: predictions using the replica method Antoine Maillard Dmitriy Kunisky 31 2 0 02 Oct 2023
Moment-Based Adjustments of Statistical Inference in High-Dimensional Generalized Linear Models Kazuma Sawaya Yoshimasa Uematsu Masaaki Imaizumi 34 2 0 28 May 2023
Injectivity of ReLU networks: perspectives from statistical physics Antoine Maillard Afonso S. Bandeira David Belius Ivan Dokmanić S. Nakajima 28 5 0 27 Feb 2023
Precise Asymptotic Analysis of Deep Random Feature Models David Bosch Ashkan Panahi B. Hassibi 35 19 0 13 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 25 35 0 01 Feb 2023
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Yan Sun Hamed Hassani 21 8 0 31 Jan 2023
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models Lijia Zhou Frederic Koehler Pragya Sur Danica J. Sutherland Nathan Srebro 83 9 0 21 Oct 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 42 121 0 03 May 2022
Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves David Bosch Ashkan Panahi Ayça Özçelikkale Devdatt Dubhash MLT 24 2 0 06 Apr 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks R. Veiga Ludovic Stephan Bruno Loureiro Florent Krzakala Lenka Zdeborová MLT 19 31 0 01 Feb 2022
The Lasso with general Gaussian designs with applications to hypothesis testing Michael Celentano Andrea Montanari Yuting Wei 42 63 0 27 Jul 2020