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Joint Embedding Self-Supervised Learning in the Kernel Regime

Joint Embedding Self-Supervised Learning in the Kernel Regime

29 September 2022
B. Kiani
Randall Balestriero
Yubei Chen
S. Lloyd
Yann LeCun
    SSL
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Papers citing "Joint Embedding Self-Supervised Learning in the Kernel Regime"

12 / 12 papers shown
Title
Navigating the Effect of Parametrization for Dimensionality Reduction
Navigating the Effect of Parametrization for Dimensionality Reduction
Haiyang Huang
Yingfan Wang
Cynthia Rudin
81
1
0
24 Nov 2024
Infinite Width Limits of Self Supervised Neural Networks
Maximilian Fleissner
Gautham Govind Anil
D. Ghoshdastidar
SSL
148
0
0
17 Nov 2024
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning:
  From InfoNCE to Kernel-Based Losses
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
40
0
0
28 May 2024
When can we Approximate Wide Contrastive Models with Neural Tangent
  Kernels and Principal Component Analysis?
When can we Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis?
Gautham Govind Anil
P. Esser
D. Ghoshdastidar
43
1
0
13 Mar 2024
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised
  Learning
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised Learning
Aarash Feizi
Randall Balestriero
Adriana Romero Soriano
Reihaneh Rabbany
26
0
0
03 Jan 2024
Non-Parametric Representation Learning with Kernels
Non-Parametric Representation Learning with Kernels
P. Esser
Maximilian Fleissner
D. Ghoshdastidar
SSL
27
4
0
05 Sep 2023
Representation Learning Dynamics of Self-Supervised Models
Representation Learning Dynamics of Self-Supervised Models
P. Esser
Satyaki Mukherjee
D. Ghoshdastidar
SSL
26
2
0
05 Sep 2023
Towards Understanding the Mechanism of Contrastive Learning via
  Similarity Structure: A Theoretical Analysis
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
26
5
0
01 Apr 2023
On the Stepwise Nature of Self-Supervised Learning
On the Stepwise Nature of Self-Supervised Learning
James B. Simon
Maksis Knutins
Liu Ziyin
Daniel Geisz
Abraham J. Fetterman
Joshua Albrecht
SSL
34
30
0
27 Mar 2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All
  You Need
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need
Vivien A. Cabannes
Léon Bottou
Yann LeCun
Randall Balestriero
45
13
0
27 Mar 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
Vivien A. Cabannes
B. Kiani
Randall Balestriero
Yann LeCun
A. Bietti
SSL
19
31
0
06 Feb 2023
With a Little Help from My Friends: Nearest-Neighbor Contrastive
  Learning of Visual Representations
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Debidatta Dwibedi
Y. Aytar
Jonathan Tompson
P. Sermanet
Andrew Zisserman
SSL
188
454
0
29 Apr 2021
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