Overfitting In Contrastive Learning?
Fuente:
arXiv
Saved in:
| Main Authors: | Rabin, Zachary, Davis, Jim, Lewis, Benjamin, Scherreik, Matthew |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Effects of Common Regularization Techniques on Open-Set Recognition
by: Rabin, Zachary, et al.
Published: (2024)
by: Rabin, Zachary, et al.
Published: (2024)
Testing for Overfitting
by: Schmidt, James
Published: (2023)
by: Schmidt, James
Published: (2023)
From Overfitting to Robustness: Quantity, Quality, and Variety Oriented Negative Sample Selection in Graph Contrastive Learning
by: Ali, Adnan, et al.
Published: (2024)
by: Ali, Adnan, et al.
Published: (2024)
Adjusted Overfitting Regression
by: Wilson, Dylan
Published: (2024)
by: Wilson, Dylan
Published: (2024)
Negotiated Representations to Prevent Overfitting in Machine Learning Applications
by: Korhan, Nuri, et al.
Published: (2023)
by: Korhan, Nuri, et al.
Published: (2023)
Harmful Overfitting in Sobolev Spaces
by: Karhadkar, Kedar, et al.
Published: (2026)
by: Karhadkar, Kedar, et al.
Published: (2026)
Countering Overfitting with Counterfactual Examples
by: Giorgi, Flavio, et al.
Published: (2025)
by: Giorgi, Flavio, et al.
Published: (2025)
PINNs Failure Modes are Overfitting
by: Andersen, Nigel T., et al.
Published: (2026)
by: Andersen, Nigel T., et al.
Published: (2026)
Borrowing From the Future: Enhancing Early Risk Assessment through Contrastive Learning
by: Sun, Minghui, et al.
Published: (2025)
by: Sun, Minghui, et al.
Published: (2025)
Control of Overfitting with Physics
by: Kozyrev, Sergei V., et al.
Published: (2024)
by: Kozyrev, Sergei V., et al.
Published: (2024)
Benign Overfitting in Single-Head Attention
by: Magen, Roey, et al.
Published: (2024)
by: Magen, Roey, et al.
Published: (2024)
Relative Overfitting and Accept-Reject Framework
by: Liu, Yanxin, et al.
Published: (2025)
by: Liu, Yanxin, et al.
Published: (2025)
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
by: Nauman, Michal, et al.
Published: (2024)
by: Nauman, Michal, et al.
Published: (2024)
Unifying and extending Precision Recall metrics for assessing generative models
by: Sykes, Benjamin, et al.
Published: (2024)
by: Sykes, Benjamin, et al.
Published: (2024)
Exploring Graph-Transformer Out-of-Distribution Generalization Abilities
by: Niv, Itay, et al.
Published: (2025)
by: Niv, Itay, et al.
Published: (2025)
Benign Overfitting with Quantum Kernels
by: Tomasi, Joachim, et al.
Published: (2025)
by: Tomasi, Joachim, et al.
Published: (2025)
Overfitting in Adaptive Robust Optimization
by: Zhu, Karl, et al.
Published: (2025)
by: Zhu, Karl, et al.
Published: (2025)
Benign Overfitting in Token Selection of Attention Mechanism
by: Sakamoto, Keitaro, et al.
Published: (2024)
by: Sakamoto, Keitaro, et al.
Published: (2024)
On Local Overfitting and Forgetting in Deep Neural Networks
by: Stern, Uri, et al.
Published: (2024)
by: Stern, Uri, et al.
Published: (2024)
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
by: Lu, Weihao, et al.
Published: (2026)
by: Lu, Weihao, et al.
Published: (2026)
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
by: Kim, Yeichan, et al.
Published: (2025)
by: Kim, Yeichan, et al.
Published: (2025)
Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers
by: Adhikari, Rabin
Published: (2025)
by: Adhikari, Rabin
Published: (2025)
More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
by: Simon, James B., et al.
Published: (2023)
by: Simon, James B., et al.
Published: (2023)
On the Existence of Optimal Transport Gradient for Learning Generative Models
by: Houdard, Antoine, et al.
Published: (2021)
by: Houdard, Antoine, et al.
Published: (2021)
Provable Weak-to-Strong Generalization via Benign Overfitting
by: Wu, David X., et al.
Published: (2024)
by: Wu, David X., et al.
Published: (2024)
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
by: Cheng, Tin Sum, et al.
Published: (2024)
by: Cheng, Tin Sum, et al.
Published: (2024)
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
by: Tang, Shange, et al.
Published: (2024)
by: Tang, Shange, et al.
Published: (2024)
Provable Tempered Overfitting of Minimal Nets and Typical Nets
by: Harel, Itamar, et al.
Published: (2024)
by: Harel, Itamar, et al.
Published: (2024)
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
by: Zhou, Lijia, et al.
Published: (2023)
by: Zhou, Lijia, et al.
Published: (2023)
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
by: Lin, Runqi, et al.
Published: (2023)
by: Lin, Runqi, et al.
Published: (2023)
Malign Overfitting: Interpolation Can Provably Preclude Invariance
by: Wald, Yoav, et al.
Published: (2022)
by: Wald, Yoav, et al.
Published: (2022)
Rethinking Benign Overfitting in Two-Layer Neural Networks
by: Xu, Ruichen, et al.
Published: (2025)
by: Xu, Ruichen, et al.
Published: (2025)
Benign Overfitting in Linear Classifiers with a Bias Term
by: Kondo, Yuta
Published: (2025)
by: Kondo, Yuta
Published: (2025)
Understanding Robust Overfitting from the Feature Generalization Perspective
by: Yu, Chaojian, et al.
Published: (2023)
by: Yu, Chaojian, et al.
Published: (2023)
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
by: Liu, Chen, et al.
Published: (2021)
by: Liu, Chen, et al.
Published: (2021)
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)
by: Laakom, Firas, et al.
Published: (2025)
Membership Inference Attacks Beyond Overfitting
by: Khalil, Mona, et al.
Published: (2025)
by: Khalil, Mona, et al.
Published: (2025)
Investigating Test Overfitting on SWE-bench
by: Ahmed, Toufique, et al.
Published: (2025)
by: Ahmed, Toufique, et al.
Published: (2025)
Overcoming Overfitting in Reinforcement Learning via Gaussian Process Diffusion Policy
by: Horprasert, Amornyos, et al.
Published: (2025)
by: Horprasert, Amornyos, et al.
Published: (2025)
Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context
by: Frei, Spencer, et al.
Published: (2024)
by: Frei, Spencer, et al.
Published: (2024)
Similar Items
-
Effects of Common Regularization Techniques on Open-Set Recognition
by: Rabin, Zachary, et al.
Published: (2024) -
Testing for Overfitting
by: Schmidt, James
Published: (2023) -
From Overfitting to Robustness: Quantity, Quality, and Variety Oriented Negative Sample Selection in Graph Contrastive Learning
by: Ali, Adnan, et al.
Published: (2024) -
Adjusted Overfitting Regression
by: Wilson, Dylan
Published: (2024) -
Negotiated Representations to Prevent Overfitting in Machine Learning Applications
by: Korhan, Nuri, et al.
Published: (2023)