A Theoretical Study of Inductive Biases in Contrastive Learning

27 November 2022

Papers citing "A Theoretical Study of Inductive Biases in Contrastive Learning"

9 / 9 papers shown

Title
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
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling Dixian Zhu Bokun Wang Zhi Chen Yaxing Wang Milan Sonka Xiaodong Wu Tianbao Yang 22 3 0 14 May 2023
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget Johannes Lehner Benedikt Alkin Andreas Fürst Elisabeth Rumetshofer Lukas Miklautz Sepp Hochreiter 26 18 0 20 Apr 2023
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
Improving Self-Supervised Learning by Characterizing Idealized Representations Yann Dubois Tatsunori Hashimoto Stefano Ermon Percy Liang SSL 83 40 0 13 Sep 2022
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Yixuan Su Fangyu Liu Zaiqiao Meng Tian Lan Lei Shu Ehsan Shareghi Nigel Collier 139 57 0 07 Nov 2021
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework Zhiyuan Li Tianhao Wang Sanjeev Arora MLT 90 98 0 13 Oct 2021
Understanding self-supervised Learning Dynamics without Contrastive Pairs Yuandong Tian Xinlei Chen Surya Ganguli SSL 138 281 0 12 Feb 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 270 3,375 0 09 Mar 2020