Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions

4 October 2022

Papers citing "Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions"

20 / 20 papers shown

Title
Contextures: Representations from Contexts Runtian Zhai Kai Yang Che-Ping Tsai Burak Varici Zico Kolter Pradeep Ravikumar 104 0 0 02 May 2025
Understanding Difficult-to-learn Examples in Contrastive Learning: A Theoretical Framework for Spectral Contrastive Learning Yi-Ge Zhang Jingyi Cui Qiran Li Yisen Wang SSL 41 0 0 03 Jan 2025
Infinite Width Limits of Self Supervised Neural Networks Maximilian Fleissner Gautham Govind Anil D. Ghoshdastidar SSL 142 0 0 17 Nov 2024
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses Panagiotis Koromilas Giorgos Bouritsas Theodoros Giannakopoulos M. Nicolaou Yannis Panagakis 32 0 0 28 May 2024
Spectrally Transformed Kernel Regression Runtian Zhai Rattana Pukdee Roger Jin Maria-Florina Balcan Pradeep Ravikumar BDL 21 2 0 01 Feb 2024
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift Saurabh Garg Amrith Rajagopal Setlur Zachary Chase Lipton Sivaraman Balakrishnan Virginia Smith Aditi Raghunathan SSL 30 6 0 06 Dec 2023
Contrastive Learning as Kernel Approximation Konstantinos Christopher Tsiolis SSL 18 0 0 06 Sep 2023
Non-Parametric Representation Learning with Kernels P. Esser Maximilian Fleissner D. Ghoshdastidar SSL 19 4 0 05 Sep 2023
Representation Learning Dynamics of Self-Supervised Models P. Esser Satyaki Mukherjee D. Ghoshdastidar SSL 19 2 0 05 Sep 2023
Rethinking Weak Supervision in Helping Contrastive Learning Jingyi Cui Weiran Huang Yifei Wang Yisen Wang NoLa SSL 32 13 0 07 Jun 2023
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression Runtian Zhai Bing Liu Andrej Risteski Zico Kolter Pradeep Ravikumar SSL 28 9 0 01 Jun 2023
The Galerkin method beats Graph-Based Approaches for Spectral Algorithms Vivien A. Cabannes Francis R. Bach 24 3 0 01 Jun 2023
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning Marina Munkhoeva Ivan V. Oseledets SSL 16 2 0 31 May 2023
Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training Utku Ozbulak Hyun Jung Lee Beril Boga Esla Timothy Anzaku Ho-min Park Arnout Van Messem W. D. Neve J. Vankerschaver DiffM 26 36 0 23 May 2023
Towards Understanding the Mechanism of Contrastive Learning via Similarity Structure: A Theoretical Analysis Hiroki Waida Yuichiro Wada Léo Andéol Takumi Nakagawa Yuhui Zhang Takafumi Kanamori SSL 21 5 0 01 Apr 2023
On the Stepwise Nature of Self-Supervised Learning James B. Simon Maksis Knutins Liu Ziyin Daniel Geisz Abraham J. Fetterman Joshua Albrecht SSL 29 29 0 27 Mar 2023
Spectral Representation Learning for Conditional Moment Models Ziyu Wang Yucen Luo Yueru Li Jun Zhu Bernhard Schölkopf CML 34 7 0 29 Oct 2022
Neural Eigenfunctions Are Structured Representation Learners Zhijie Deng Jiaxin Shi Hao Zhang Peng Cui Cewu Lu Jun Zhu 45 14 0 23 Oct 2022
Spectral Inference Networks: Unifying Deep and Spectral Learning David Pfau Stig Petersen Ashish Agarwal David Barrett Kimberly L. Stachenfeld 49 40 0 06 Jun 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 230 31,253 0 16 Jan 2013