An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Cui, Jingyi, Wen, Hongwei, Wang, Yisen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Augmentation Overlap Theory of Contrastive Learning
by: Zhang, Qi, et al.
Published: (2025)
by: Zhang, Qi, et al.
Published: (2025)
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
by: Cui, Jingyi, et al.
Published: (2025)
by: Cui, Jingyi, et al.
Published: (2025)
Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
by: Zhang, Yi-Ge, et al.
Published: (2025)
by: Zhang, Yi-Ge, et al.
Published: (2025)
On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy
by: Cui, Jingyi, et al.
Published: (2025)
by: Cui, Jingyi, et al.
Published: (2025)
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
by: Luthra, Achleshwar, et al.
Published: (2025)
by: Luthra, Achleshwar, et al.
Published: (2025)
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)
by: Jian, Xiangru, et al.
Published: (2024)
Bayesian Self-Supervised Contrastive Learning
by: Liu, Bin, et al.
Published: (2023)
by: Liu, Bin, et al.
Published: (2023)
On the Alignment Between Supervised and Self-Supervised Contrastive Learning
by: Luthra, Achleshwar, et al.
Published: (2025)
by: Luthra, Achleshwar, et al.
Published: (2025)
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
by: Qiu, Shuang, et al.
Published: (2022)
by: Qiu, Shuang, et al.
Published: (2022)
A Generalized Learning Framework for Self-Supervised Contrastive Learning
by: Si, Lingyu, et al.
Published: (2025)
by: Si, Lingyu, et al.
Published: (2025)
Do Generated Data Always Help Contrastive Learning?
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima
by: Tang, Yiming, et al.
Published: (2025)
by: Tang, Yiming, et al.
Published: (2025)
Non-negative Contrastive Learning
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Contrastive Self-Supervised Learning at the Edge: An Energy Perspective
by: Famá, Fernanda, et al.
Published: (2025)
by: Famá, Fernanda, et al.
Published: (2025)
Collapse-Proof Non-Contrastive Self-Supervised Learning
by: Sansone, Emanuele, et al.
Published: (2024)
by: Sansone, Emanuele, et al.
Published: (2024)
Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering
by: Zhao, Tianxiang, et al.
Published: (2025)
by: Zhao, Tianxiang, et al.
Published: (2025)
Understanding Self-supervised Contrastive Learning through Supervised Objectives
by: Lee, Byeongchan
Published: (2025)
by: Lee, Byeongchan
Published: (2025)
Self-Supervised Learning for User Localization
by: Dash, Ankan, et al.
Published: (2024)
by: Dash, Ankan, et al.
Published: (2024)
Dual Perspectives on Non-Contrastive Self-Supervised Learning
by: Ponce, Jean, et al.
Published: (2025)
by: Ponce, Jean, et al.
Published: (2025)
Self-Supervised Contrastive Learning for Long-term Forecasting
by: Park, Junwoo, et al.
Published: (2024)
by: Park, Junwoo, et al.
Published: (2024)
Deep Augmentation: Dropout as Augmentation for Self-Supervised Learning
by: Brüel-Gabrielsson, Rickard, et al.
Published: (2023)
by: Brüel-Gabrielsson, Rickard, et al.
Published: (2023)
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
by: Thimonier, Hugo, et al.
Published: (2024)
by: Thimonier, Hugo, et al.
Published: (2024)
Contrastive and Variational Approaches in Self-Supervised Learning for Complex Data Mining
by: Liang, Yingbin, et al.
Published: (2025)
by: Liang, Yingbin, et al.
Published: (2025)
Weak Augmentation Guided Relational Self-Supervised Learning
by: Zheng, Mingkai, et al.
Published: (2022)
by: Zheng, Mingkai, et al.
Published: (2022)
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning
by: Gao, Xinyi, et al.
Published: (2024)
by: Gao, Xinyi, et al.
Published: (2024)
A Theoretical Characterization of Optimal Data Augmentations in Self-Supervised Learning
by: Feigin, Shlomo Libo, et al.
Published: (2024)
by: Feigin, Shlomo Libo, et al.
Published: (2024)
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
by: Zhang, Qi, et al.
Published: (2024)
by: Zhang, Qi, et al.
Published: (2024)
Contrastive Self-Supervised Learning As Neural Manifold Packing
by: Zhang, Guanming, et al.
Published: (2025)
by: Zhang, Guanming, et al.
Published: (2025)
Self-Supervised Learning for Time Series: Contrastive or Generative?
by: Liu, Ziyu, et al.
Published: (2024)
by: Liu, Ziyu, et al.
Published: (2024)
Dynamically Scaled Temperature in Self-Supervised Contrastive Learning
by: Manna, Siladittya, et al.
Published: (2023)
by: Manna, Siladittya, et al.
Published: (2023)
Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework
by: Luo, Shiyuan, et al.
Published: (2025)
by: Luo, Shiyuan, et al.
Published: (2025)
PASCL: Supervised Contrastive Learning with Perturbative Augmentation for Particle Decay Reconstruction
by: Lu, Junjian, et al.
Published: (2024)
by: Lu, Junjian, et al.
Published: (2024)
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025)
by: Xie, Shifeng, et al.
Published: (2025)
Self-Supervised Transformer-based Contrastive Learning for Intrusion Detection Systems
by: Koukoulis, Ippokratis, et al.
Published: (2025)
by: Koukoulis, Ippokratis, et al.
Published: (2025)
Multi-level Supervised Contrastive Learning
by: Ghanooni, Naghmeh, et al.
Published: (2025)
by: Ghanooni, Naghmeh, et al.
Published: (2025)
Weakly-Supervised Contrastive Learning for Imprecise Class Labels
by: Zhou, Zi-Hao, et al.
Published: (2025)
by: Zhou, Zi-Hao, et al.
Published: (2025)
Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis
by: Ren, Junyu, et al.
Published: (2026)
by: Ren, Junyu, et al.
Published: (2026)
CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning
by: Qin, Bin, et al.
Published: (2025)
by: Qin, Bin, et al.
Published: (2025)
Parametric Augmentation for Time Series Contrastive Learning
by: Zheng, Xu, et al.
Published: (2024)
by: Zheng, Xu, et al.
Published: (2024)
Self-Supervised Contrastive Pre-Training for Multivariate Point Processes
by: Shou, Xiao, et al.
Published: (2024)
by: Shou, Xiao, et al.
Published: (2024)
Similar Items
-
An Augmentation Overlap Theory of Contrastive Learning
by: Zhang, Qi, et al.
Published: (2025) -
An Inclusive Theoretical Framework of Robust Supervised Contrastive Loss against Label Noise
by: Cui, Jingyi, et al.
Published: (2025) -
Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
by: Zhang, Yi-Ge, et al.
Published: (2025) -
On the Limits of Sparse Autoencoders: A Theoretical Framework and Reweighted Remedy
by: Cui, Jingyi, et al.
Published: (2025) -
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
by: Luthra, Achleshwar, et al.
Published: (2025)