Do More Negative Samples Necessarily Hurt in Contrastive Learning?

3 May 2022

Papers citing "Do More Negative Samples Necessarily Hurt in Contrastive Learning?"

26 / 26 papers shown

Title
SuperRAG: Beyond RAG with Layout-Aware Graph Modeling Jeff Yang Duy-Khanh Vu Minh-Tien Nguyen Xuan-Quang Nguyen Linh Nguyen H. Le 3DV 63 0 0 28 Feb 2025
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis Satoki Ishikawa Makoto Yamada Han Bao Yuki Takezawa 50 0 0 23 May 2024
Semantic Feature Learning for Universal Unsupervised Cross-Domain Retrieval Lixu Wang Xinyu Du Qi Zhu 21 0 0 08 Mar 2024
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 26 9 0 27 Feb 2024
Analysis of Using Sigmoid Loss for Contrastive Learning Chungpa Lee Joonhwan Chang Jy-yong Sohn 35 2 0 20 Feb 2024
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 17 1 0 14 Feb 2024
Optimal Sample Complexity of Contrastive Learning Noga Alon Dmitrii Avdiukhin Dor Elboim Orr Fischer G. Yaroslavtsev SSL 8 1 0 01 Dec 2023
Contrastive Learning for Inference in Dialogue Etsuko Ishii Yan Xu Bryan Wilie Ziwei Ji Holy Lovenia Willy Chung Pascale Fung 13 0 0 19 Oct 2023
Feature Normalization Prevents Collapse of Non-contrastive Learning Dynamics Han Bao SSL MLT 10 1 0 28 Sep 2023
Headless Language Models: Learning without Predicting with Contrastive Weight Tying Nathan Godey Eric Villemonte de la Clergerie Benoît Sagot 18 3 0 15 Sep 2023
Unsupervised Representation Learning for Time Series: A Review Qianwen Meng Hangwei Qian Yong Liu Yonghui Xu Zhiqi Shen Li-zhen Cui AI4TS 25 17 0 03 Aug 2023
Towards the Sparseness of Projection Head in Self-Supervised Learning Zeen Song Xingzhe Su Jingyao Wang Wenwen Qiang Changwen Zheng Fuchun Sun 15 3 0 18 Jul 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 19 5 0 01 Apr 2023
InfoNCE Loss Provably Learns Cluster-Preserving Representations Advait Parulekar Liam Collins Karthikeyan Shanmugam Aryan Mokhtari Sanjay Shakkottai SSL 24 12 0 15 Feb 2023
Contrastive Learning with Consistent Representations Zihu Wang Yu Wang Hanbin Hu Peng Li CLL 16 5 0 03 Feb 2023
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 13 15 0 04 Jan 2023
SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes Nicolas Larue Ngoc-Son Vu Vitomir Štruc Peter Peer V. Christophides AAML 20 27 0 21 Nov 2022
On Negative Sampling for Contrastive Audio-Text Retrieval Huang Xie Okko Rasanen Tuomas Virtanen 12 6 0 08 Nov 2022
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 17 1 0 31 Oct 2022
FG-UAP: Feature-Gathering Universal Adversarial Perturbation Zhixing Ye Xinwen Cheng X. Huang AAML 38 9 0 27 Sep 2022
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois Tatsunori Hashimoto Stefano Ermon Percy Liang SSL 59 40 0 13 Sep 2022
On the Surrogate Gap between Contrastive and Supervised Losses Han Bao Yoshihiro Nagano Kento Nozawa SSL UQCV 10 19 0 06 Oct 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 236 206 0 17 Feb 2021
Understanding self-supervised Learning Dynamics without Contrastive Pairs Yuandong Tian Xinlei Chen Surya Ganguli SSL 132 278 0 12 Feb 2021
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 29,632 0 16 Jan 2013
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 109 253 0 10 Dec 2012