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Investigating the Role of Negatives in Contrastive Representation
  Learning

Investigating the Role of Negatives in Contrastive Representation Learning

18 June 2021
Jordan T. Ash
Surbhi Goel
A. Krishnamurthy
Dipendra Kumar Misra
    SSL
ArXivPDFHTML

Papers citing "Investigating the Role of Negatives in Contrastive Representation Learning"

42 / 42 papers shown
Title
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
43
0
0
03 Jan 2025
Does Negative Sampling Matter? A Review with Insights into its Theory
  and Applications
Does Negative Sampling Matter? A Review with Insights into its Theory and Applications
Zhen Yang
Ming Ding
Tinglin Huang
Yukuo Cen
Junshuai Song
Bin Xu
Yuxiao Dong
Jie Tang
33
9
0
27 Feb 2024
DUEL: Duplicate Elimination on Active Memory for Self-Supervised
  Class-Imbalanced Learning
DUEL: Duplicate Elimination on Active Memory for Self-Supervised Class-Imbalanced Learning
Won-Seok Choi
Hyun-Dong Lee
Dong-Sig Han
Junseok Park
Heeyeon Koo
Byoung-Tak Zhang
30
1
0
14 Feb 2024
Optimal Sample Complexity of Contrastive Learning
Optimal Sample Complexity of Contrastive Learning
Noga Alon
Dmitrii Avdiukhin
Dor Elboim
Orr Fischer
G. Yaroslavtsev
SSL
22
5
0
01 Dec 2023
Identifiable Contrastive Learning with Automatic Feature Importance
  Discovery
Identifiable Contrastive Learning with Automatic Feature Importance Discovery
Qi Zhang
Yifei Wang
Yisen Wang
26
12
0
29 Oct 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
28
0
0
23 Oct 2023
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu
Huayi Tang
Yong Liu
26
2
0
06 Oct 2023
Certifiably Robust Graph Contrastive Learning
Certifiably Robust Graph Contrastive Learning
Min Lin
Teng Xiao
Enyan Dai
Xiang Zhang
Suhang Wang
AAML
24
6
0
05 Oct 2023
Headless Language Models: Learning without Predicting with Contrastive
  Weight Tying
Headless Language Models: Learning without Predicting with Contrastive Weight Tying
Nathan Godey
Eric Villemonte de la Clergerie
Benoît Sagot
34
3
0
15 Sep 2023
Towards a Rigorous Analysis of Mutual Information in Contrastive
  Learning
Towards a Rigorous Analysis of Mutual Information in Contrastive Learning
Kyungeun Lee
Jaeill Kim
Suhyun Kang
Wonjong Rhee
SSL
30
2
0
30 Aug 2023
Unsupervised Representation Learning for Time Series: A Review
Unsupervised Representation Learning for Time Series: A Review
Qianwen Meng
Hangwei Qian
Yong Liu
Yonghui Xu
Zhiqi Shen
Li-zhen Cui
AI4TS
30
17
0
03 Aug 2023
Towards the Sparseness of Projection Head in Self-Supervised Learning
Towards the Sparseness of Projection Head in Self-Supervised Learning
Zeen Song
Xingzhe Su
Jingyao Wang
Wenwen Qiang
Changwen Zheng
Fuchun Sun
33
3
0
18 Jul 2023
Rethinking Weak Supervision in Helping Contrastive Learning
Rethinking Weak Supervision in Helping Contrastive Learning
Jingyi Cui
Weiran Huang
Yifei Wang
Yisen Wang
NoLa
SSL
32
13
0
07 Jun 2023
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised
  Attention Multiple Instance Learning
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning
Zhe Huang
B. Wessler
M. C. Hughes
22
3
0
25 May 2023
Sample and Predict Your Latent: Modality-free Sequential Disentanglement
  via Contrastive Estimation
Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
Ilana D Naiman
Nimrod Berman
Omri Azencot
DRL
26
6
0
25 May 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
21
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
32
29
0
27 Mar 2023
Towards a Unified Theoretical Understanding of Non-contrastive Learning
  via Rank Differential Mechanism
Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
Zhijian Zhuo
Yifei Wang
Jinwen Ma
Yisen Wang
45
24
0
04 Mar 2023
ArCL: Enhancing Contrastive Learning with Augmentation-Robust
  Representations
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
Xuyang Zhao
Tianqi Du
Yisen Wang
Jun Yao
Weiran Huang
36
13
0
02 Mar 2023
Generalization Analysis for Contrastive Representation Learning
Generalization Analysis for Contrastive Representation Learning
Yunwen Lei
Tianbao Yang
Yiming Ying
Ding-Xuan Zhou
28
8
0
24 Feb 2023
InfoNCE Loss Provably Learns Cluster-Preserving Representations
InfoNCE Loss Provably Learns Cluster-Preserving Representations
Advait Parulekar
Liam Collins
Karthikeyan Shanmugam
Aryan Mokhtari
Sanjay Shakkottai
SSL
34
20
0
15 Feb 2023
Understanding Multimodal Contrastive Learning and Incorporating Unpaired
  Data
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
Ryumei Nakada
Halil Ibrahim Gulluk
Zhun Deng
Wenlong Ji
James Y. Zou
Linjun Zhang
SSL
VLM
42
34
0
13 Feb 2023
MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain
  Adaptation for Breast MRI Segmentation in Small Datasets
MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasets
Sheng Kuang
Henry C. Woodruff
R. Granzier
T. Nijnatten
M. Lobbes
M. Smidt
Philippe Lambin
S. Mehrkanoon
25
16
0
04 Jan 2023
A Theoretical Study of Inductive Biases in Contrastive Learning
A Theoretical Study of Inductive Biases in Contrastive Learning
Jeff Z. HaoChen
Tengyu Ma
UQCV
SSL
33
31
0
27 Nov 2022
DUEL: Adaptive Duplicate Elimination on Working Memory for
  Self-Supervised Learning
DUEL: Adaptive Duplicate Elimination on Working Memory for Self-Supervised Learning
Won-Seok Choi
Dong-Sig Han
Hyun-Dong Lee
Junseok Park
Byoung-Tak Zhang
30
1
0
31 Oct 2022
Multiple Instance Learning via Iterative Self-Paced Supervised
  Contrastive Learning
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning
Kangning Liu
Weicheng Zhu
Yiqiu Shen
Sheng Liu
N. Razavian
Krzysztof J. Geras
C. Fernandez‐Granda
SSL
28
24
0
17 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
Improving Self-Supervised Learning by Characterizing Idealized
  Representations
Improving Self-Supervised Learning by Characterizing Idealized Representations
Yann Dubois
Tatsunori Hashimoto
Stefano Ermon
Percy Liang
SSL
73
40
0
13 Sep 2022
ProtoCLIP: Prototypical Contrastive Language Image Pretraining
ProtoCLIP: Prototypical Contrastive Language Image Pretraining
Delong Chen
Zhao Wu
Fan Liu
Zaiquan Yang
Huaxi Huang
Ying Tan
Erjin Zhou
VLM
CLIP
27
28
0
22 Jun 2022
From $t$-SNE to UMAP with contrastive learning
From ttt-SNE to UMAP with contrastive learning
Sebastian Damrich
Jan Niklas Böhm
Fred Hamprecht
D. Kobak
SSL
32
19
0
03 Jun 2022
The Mechanism of Prediction Head in Non-contrastive Self-supervised
  Learning
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen
Yuanzhi Li
SSL
27
34
0
12 May 2022
Do More Negative Samples Necessarily Hurt in Contrastive Learning?
Do More Negative Samples Necessarily Hurt in Contrastive Learning?
Pranjal Awasthi
Nishanth Dikkala
Pritish Kamath
30
40
0
03 May 2022
Chaos is a Ladder: A New Theoretical Understanding of Contrastive
  Learning via Augmentation Overlap
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap
Yifei Wang
Qi Zhang
Yisen Wang
Jiansheng Yang
Zhouchen Lin
19
98
0
25 Mar 2022
Understanding Contrastive Learning Requires Incorporating Inductive
  Biases
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Saunshi
Jordan T. Ash
Surbhi Goel
Dipendra Kumar Misra
Cyril Zhang
Sanjeev Arora
Sham Kakade
A. Krishnamurthy
SSL
19
109
0
28 Feb 2022
Augmentations in Graph Contrastive Learning: Current Methodological
  Flaws & Towards Better Practices
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices
Puja Trivedi
Ekdeep Singh Lubana
Yujun Yan
Yaoqing Yang
Danai Koutra
37
52
0
05 Nov 2021
Towards the Generalization of Contrastive Self-Supervised Learning
Towards the Generalization of Contrastive Self-Supervised Learning
Weiran Huang
Mingyang Yi
Xuyang Zhao
Zihao Jiang
SSL
21
105
0
01 Nov 2021
On the Surrogate Gap between Contrastive and Supervised Losses
On the Surrogate Gap between Contrastive and Supervised Losses
Han Bao
Yoshihiro Nagano
Kento Nozawa
SSL
UQCV
41
19
0
06 Oct 2021
Understanding Negative Samples in Instance Discriminative
  Self-supervised Representation Learning
Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
Kento Nozawa
Issei Sato
SSL
20
43
0
13 Feb 2021
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
279
0
12 Feb 2021
LRC-BERT: Latent-representation Contrastive Knowledge Distillation for
  Natural Language Understanding
LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding
Hao Fu
Shaojun Zhou
Qihong Yang
Junjie Tang
Guiquan Liu
Kaikui Liu
Xiaolong Li
34
57
0
14 Dec 2020
Contrastive Representation Learning: A Framework and Review
Contrastive Representation Learning: A Framework and Review
Phúc H. Lê Khắc
Graham Healy
A. Smeaton
SSL
AI4TS
164
684
0
10 Oct 2020
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
233
31,253
0
16 Jan 2013
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