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Contrasting quadratic assignments for set-based representation learning

Contrasting quadratic assignments for set-based representation learning

31 May 2022
A. Moskalev
Ivan Sosnovik
Volker Fischer
A. Smeulders
    SSL
ArXivPDFHTML

Papers citing "Contrasting quadratic assignments for set-based representation learning"

32 / 32 papers shown
Title
ScaleNet: An Unsupervised Representation Learning Method for Limited
  Information
ScaleNet: An Unsupervised Representation Learning Method for Limited Information
Huili Huang
M. M. Roozbahani
SSL
93
804
0
03 Oct 2023
VICReg: Variance-Invariance-Covariance Regularization for
  Self-Supervised Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes
Jean Ponce
Yann LeCun
SSL
DML
153
933
0
11 May 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
307
2,347
0
04 Mar 2021
Boosting Contrastive Self-Supervised Learning with False Negative
  Cancellation
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation
T. Huynh
Simon Kornblith
Matthew R. Walter
Michael Maire
M. Khademi
SSL
73
168
0
23 Nov 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
253
4,054
0
20 Nov 2020
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
Dense Contrastive Learning for Self-Supervised Visual Pre-Training
Xinlong Wang
Rufeng Zhang
Chunhua Shen
Tao Kong
Lei Li
SSL
77
686
0
18 Nov 2020
Intriguing Properties of Contrastive Losses
Intriguing Properties of Contrastive Losses
Ting Chen
Calvin Luo
Lala Li
66
175
0
05 Nov 2020
A Survey on Contrastive Self-supervised Learning
A Survey on Contrastive Self-supervised Learning
Ashish Jaiswal
Ashwin Ramesh Babu
Mohammad Zaki Zadeh
Debapriya Banerjee
F. Makedon
SSL
127
1,394
0
31 Oct 2020
Whitening for Self-Supervised Representation Learning
Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov
Aliaksandr Siarohin
E. Sangineto
N. Sebe
SSL
89
313
0
13 Jul 2020
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCL
SSL
230
4,083
0
17 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
368
6,806
0
13 Jun 2020
Self-Supervised Relational Reasoning for Representation Learning
Self-Supervised Relational Reasoning for Representation Learning
Massimiliano Patacchiola
Amos Storkey
OOD
SSL
53
63
0
10 Jun 2020
Understanding Contrastive Representation Learning through Alignment and
  Uniformity on the Hypersphere
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang
Phillip Isola
SSL
154
1,840
0
20 May 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
481
3,433
0
09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
369
18,778
0
13 Feb 2020
Self-Supervised Learning of Pretext-Invariant Representations
Self-Supervised Learning of Pretext-Invariant Representations
Ishan Misra
Laurens van der Maaten
SSL
VLM
103
1,453
0
04 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
199
12,085
0
13 Nov 2019
On Mutual Information Maximization for Representation Learning
On Mutual Information Maximization for Representation Learning
Michael Tschannen
Josip Djolonga
Paul Kishan Rubenstein
Sylvain Gelly
Mario Lucic
SSL
174
495
0
31 Jul 2019
Revisiting Self-Supervised Visual Representation Learning
Revisiting Self-Supervised Visual Representation Learning
Alexander Kolesnikov
Xiaohua Zhai
Lucas Beyer
SSL
145
716
0
25 Jan 2019
Learning with Fenchel-Young Losses
Learning with Fenchel-Young Losses
Mathieu Blondel
André F. T. Martins
Vlad Niculae
143
136
0
08 Jan 2019
Learning deep representations by mutual information estimation and
  maximization
Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm
A. Fedorov
Samuel Lavoie-Marchildon
Karan Grewal
Phil Bachman
Adam Trischler
Yoshua Bengio
SSL
DRL
320
2,662
0
20 Aug 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRL
SSL
320
10,302
0
10 Jul 2018
Learning Classifiers with Fenchel-Young Losses: Generalized Entropies,
  Margins, and Algorithms
Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms
Mathieu Blondel
André F. T. Martins
Vlad Niculae
FedML
37
39
0
24 May 2018
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OOD
SSL
DRL
252
3,290
0
21 Mar 2018
SparseMAP: Differentiable Sparse Structured Inference
SparseMAP: Differentiable Sparse Structured Inference
Vlad Niculae
André F. T. Martins
Mathieu Blondel
Claire Cardie
43
123
0
12 Feb 2018
In Defense of the Triplet Loss for Person Re-Identification
In Defense of the Triplet Loss for Person Re-Identification
Alexander Hermans
Lucas Beyer
Bastian Leibe
DML
78
3,206
0
22 Mar 2017
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
333
8,130
0
13 Aug 2016
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label
  Classification
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
André F. T. Martins
Ramón Fernández Astudillo
176
725
0
05 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
362
19,660
0
09 Mar 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
677
31,512
0
16 Jan 2013
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