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Provable Guarantees for Self-Supervised Deep Learning with Spectral
  Contrastive Loss

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss

8 June 2021
Jeff Z. HaoChen
Colin Wei
Adrien Gaidon
Tengyu Ma
    SSL
ArXivPDFHTML

Papers citing "Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss"

50 / 77 papers shown
Title
seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models
seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models
Hafez Ghaemi
Eilif Muller
Shahab Bakhtiari
49
0
0
06 May 2025
Contextures: Representations from Contexts
Contextures: Representations from Contexts
Runtian Zhai
Kai Yang
Che-Ping Tsai
Burak Varici
Zico Kolter
Pradeep Ravikumar
119
0
0
02 May 2025
THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings
THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings
Bowen Deng
Tong Wang
Lele Fu
Sheng Huang
Chuan Chen
Tao Zhang
87
0
0
17 Feb 2025
Structure-preserving contrastive learning for spatial time series
Structure-preserving contrastive learning for spatial time series
Yiru Jiao
S. Cranenburgh
Simeon C. Calvert
H. Lint
AI4TS
92
0
0
10 Feb 2025
Enhancing Graph Self-Supervised Learning with Graph Interplay
Enhancing Graph Self-Supervised Learning with Graph Interplay
Xinjian Zhao
Wei Pang
Xiangru Jian
Yaoyao Xu
Chaolong Ying
Tianshu Yu
51
0
0
17 Jan 2025
Infinite Width Limits of Self Supervised Neural Networks
Maximilian Fleissner
Gautham Govind Anil
D. Ghoshdastidar
SSL
148
0
0
17 Nov 2024
Past, Present, and Future of Sensor-Based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task
Past, Present, and Future of Sensor-Based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task
H. Haresamudram
Chi Ian Tang
Sungho Suh
P. Lukowicz
Thomas Ploetz
76
2
0
11 Nov 2024
Investigating the Impact of Model Complexity in Large Language Models
Investigating the Impact of Model Complexity in Large Language Models
Jing Luo
Huiyuan Wang
Weiran Huang
36
0
0
01 Oct 2024
On the Role of Discrete Tokenization in Visual Representation Learning
On the Role of Discrete Tokenization in Visual Representation Learning
Tianqi Du
Yifei Wang
Yisen Wang
52
7
0
12 Jul 2024
Look Ahead or Look Around? A Theoretical Comparison Between
  Autoregressive and Masked Pretraining
Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining
Qi Zhang
Tianqi Du
Haotian Huang
Yifei Wang
Yisen Wang
39
3
0
01 Jul 2024
InfoNCE: Identifying the Gap Between Theory and Practice
InfoNCE: Identifying the Gap Between Theory and Practice
E. Rusak
Patrik Reizinger
Attila Juhos
Oliver Bringmann
Roland S. Zimmermann
Wieland Brendel
35
5
0
28 Jun 2024
Theoretical Analysis of Weak-to-Strong Generalization
Theoretical Analysis of Weak-to-Strong Generalization
Hunter Lang
David Sontag
Aravindan Vijayaraghavan
25
20
0
25 May 2024
Better Representations via Adversarial Training in Pre-Training: A
  Theoretical Perspective
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
Yue Xing
Xiaofeng Lin
Qifan Song
Yi Tian Xu
Belinda Zeng
Guang Cheng
SSL
26
0
0
26 Jan 2024
Preserving Silent Features for Domain Generalization
Preserving Silent Features for Domain Generalization
Chujie Zhao
Tianren Zhang
Feng Chen
23
0
0
06 Jan 2024
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL
  Architectures
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
Vimal Thilak
Chen Huang
Omid Saremi
Laurent Dinh
Hanlin Goh
Preetum Nakkiran
Josh Susskind
Etai Littwin
23
7
0
07 Dec 2023
Towards a Unified Framework of Contrastive Learning for Disentangled
  Representations
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes
Zhiwei Han
Hao Shen
34
4
0
08 Nov 2023
Graph Ranking Contrastive Learning: A Extremely Simple yet Efficient
  Method
Graph Ranking Contrastive Learning: A Extremely Simple yet Efficient Method
Yulan Hu
Ouyang Sheng
Jingyu Liu
Ge Chen
Zhirui Yang
Junchen Wan
Fuzheng Zhang
Zhongyuan Wang
Yong Liu
31
0
0
23 Oct 2023
Towards the Sparseness of Projection Head in Self-Supervised Learning
Towards the Sparseness of Projection Head in Self-Supervised Learning
Changwen Zheng
Xingzhe Su
Wenwen Qiang
Jingyao Wang
Changwen Zheng
Gang Hua
36
3
0
18 Jul 2023
Understanding Contrastive Learning Through the Lens of Margins
Understanding Contrastive Learning Through the Lens of Margins
Daniel Rho
Taesoo Kim
Sooill Park
Jaehyun Park
Jaehan Park
SSL
32
2
0
20 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from
  Expansion and Shrinkage
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage
Yu Gui
Cong Ma
Yiqiao Zhong
22
6
0
06 Jun 2023
Quantifying Representation Reliability in Self-Supervised Learning
  Models
Quantifying Representation Reliability in Self-Supervised Learning Models
Young-Jin Park
Hao Wang
Shervin Ardeshir
Navid Azizan
SSL
UQCV
31
3
0
31 May 2023
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in
  Self-Supervised Learning
Spectal Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
Marina Munkhoeva
Ivan V. Oseledets
SSL
31
2
0
31 May 2023
Incomplete Multi-view Clustering via Diffusion Completion
Incomplete Multi-view Clustering via Diffusion Completion
Sifan Fang
DiffM
16
4
0
19 May 2023
How does Contrastive Learning Organize Images?
How does Contrastive Learning Organize Images?
Yunzhe Zhang
Yao Lu
Qi Xuan
SSL
32
0
0
17 May 2023
Denoising Cosine Similarity: A Theory-Driven Approach for Efficient
  Representation Learning
Denoising Cosine Similarity: A Theory-Driven Approach for Efficient Representation Learning
Takumi Nakagawa
Y. Sanada
Hiroki Waida
Yuhui Zhang
Yuichiro Wada
K. Takanashi
Tomonori Yamada
Takafumi Kanamori
DiffM
19
5
0
19 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
37
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
Contrastive Learning Is Spectral Clustering On Similarity Graph
Contrastive Learning Is Spectral Clustering On Similarity Graph
Zhi-Hao Tan
Yifan Zhang
Jingqin Yang
Yang Yuan
SSL
54
18
0
27 Mar 2023
Multi-view Feature Extraction based on Triple Contrastive Heads
Multi-view Feature Extraction based on Triple Contrastive Heads
Hongjie Zhang
11
0
0
22 Mar 2023
Preventing Dimensional Collapse of Incomplete Multi-View Clustering via
  Direct Contrastive Learning
Preventing Dimensional Collapse of Incomplete Multi-View Clustering via Direct Contrastive Learning
Kaiwu Zhang
Shiqiang Du
Bao-Yu Liu
Shengxia Gao
19
0
0
22 Mar 2023
On the Provable Advantage of Unsupervised Pretraining
On the Provable Advantage of Unsupervised Pretraining
Jiawei Ge
Shange Tang
Jianqing Fan
Chi Jin
SSL
33
16
0
02 Mar 2023
Unsupervised Learning on a DIET: Datum IndEx as Target Free of
  Self-Supervision, Reconstruction, Projector Head
Unsupervised Learning on a DIET: Datum IndEx as Target Free of Self-Supervision, Reconstruction, Projector Head
Randall Balestriero
38
3
0
20 Feb 2023
Self-supervised learning of Split Invariant Equivariant representations
Self-supervised learning of Split Invariant Equivariant representations
Q. Garrido
Laurent Najman
Yann LeCun
SSL
29
32
0
14 Feb 2023
Multi-view Feature Extraction based on Dual Contrastive Head
Multi-view Feature Extraction based on Dual Contrastive Head
Hongjie Zhang
18
1
0
08 Feb 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
Revisiting Discriminative vs. Generative Classifiers: Theory and
  Implications
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
Chenyu Zheng
Guoqiang Wu
Fan Bao
Yue Cao
Chongxuan Li
Jun Zhu
BDL
30
30
0
05 Feb 2023
Deciphering the Projection Head: Representation Evaluation
  Self-supervised Learning
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning
Jiajun Ma
Tianyang Hu
Wenjia Wang
17
8
0
28 Jan 2023
GEDI: GEnerative and DIscriminative Training for Self-Supervised
  Learning
GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning
Emanuele Sansone
Robin Manhaeve
SSL
20
9
0
27 Dec 2022
On minimal variations for unsupervised representation learning
On minimal variations for unsupervised representation learning
Vivien A. Cabannes
A. Bietti
Randall Balestriero
SSL
DRL
25
8
0
07 Nov 2022
Contrastive Value Learning: Implicit Models for Simple Offline RL
Contrastive Value Learning: Implicit Models for Simple Offline RL
Bogdan Mazoure
Benjamin Eysenbach
Ofir Nachum
Jonathan Tompson
SSL
OffRL
38
7
0
03 Nov 2022
Augmentation Invariant Manifold Learning
Augmentation Invariant Manifold Learning
Shulei Wang
36
1
0
01 Nov 2022
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for
  Language Models
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models
Hong Liu
Sang Michael Xie
Zhiyuan Li
Tengyu Ma
AI4CE
40
49
0
25 Oct 2022
The Curious Case of Benign Memorization
The Curious Case of Benign Memorization
Sotiris Anagnostidis
Gregor Bachmann
Lorenzo Noci
Thomas Hofmann
AAML
49
8
0
25 Oct 2022
Label Propagation with Weak Supervision
Label Propagation with Weak Supervision
Rattana Pukdee
Dylan Sam
Maria-Florina Balcan
Pradeep Ravikumar
37
9
0
07 Oct 2022
RankMe: Assessing the downstream performance of pretrained
  self-supervised representations by their rank
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank
Q. Garrido
Randall Balestriero
Laurent Najman
Yann LeCun
SSL
53
73
0
05 Oct 2022
What shapes the loss landscape of self-supervised learning?
What shapes the loss landscape of self-supervised learning?
Liu Ziyin
Ekdeep Singh Lubana
Masakuni Ueda
Hidenori Tanaka
50
20
0
02 Oct 2022
Minimalistic Unsupervised Learning with the Sparse Manifold Transform
Minimalistic Unsupervised Learning with the Sparse Manifold Transform
Yubei Chen
Zeyu Yun
Y. Ma
Bruno A. Olshausen
Yann LeCun
52
8
0
30 Sep 2022
Variance Covariance Regularization Enforces Pairwise Independence in
  Self-Supervised Representations
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations
Grégoire Mialon
Randall Balestriero
Yann LeCun
29
9
0
29 Sep 2022
Joint Embedding Self-Supervised Learning in the Kernel Regime
Joint Embedding Self-Supervised Learning in the Kernel Regime
B. Kiani
Randall Balestriero
Yubei Chen
S. Lloyd
Yann LeCun
SSL
46
13
0
29 Sep 2022
The Geometry of Self-supervised Learning Models and its Impact on
  Transfer Learning
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning
Romain Cosentino
Sarath Shekkizhar
Mahdi Soltanolkotabi
A. Avestimehr
Antonio Ortega
SSL
51
7
0
18 Sep 2022
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