Instance-dependent Early Stopping
Fuente:
arXiv
Guardado en:
| Autores principales: | Yuan, Suqin, Lin, Runqi, Feng, Lei, Han, Bo, Liu, Tongliang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Early Stopping Against Label Noise Without Validation Data
por: Yuan, Suqin, et al.
Publicado: (2025)
por: Yuan, Suqin, et al.
Publicado: (2025)
Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
por: Yuan, Suqin, et al.
Publicado: (2025)
por: Yuan, Suqin, et al.
Publicado: (2025)
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
por: Lin, Runqi, et al.
Publicado: (2023)
por: Lin, Runqi, et al.
Publicado: (2023)
FORCE: Transferable Visual Jailbreaking Attacks via Feature Over-Reliance CorrEction
por: Lin, Runqi, et al.
Publicado: (2025)
por: Lin, Runqi, et al.
Publicado: (2025)
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
por: Lin, Runqi, et al.
Publicado: (2024)
por: Lin, Runqi, et al.
Publicado: (2024)
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
por: Lin, Runqi, et al.
Publicado: (2024)
por: Lin, Runqi, et al.
Publicado: (2024)
Mitigating Mismatch within Reference-based Preference Optimization
por: Yuan, Suqin, et al.
Publicado: (2026)
por: Yuan, Suqin, et al.
Publicado: (2026)
Time-Efficient Evaluation and Enhancement of Adversarial Robustness in Deep Neural Networks
por: Lin, Runqi
Publicado: (2025)
por: Lin, Runqi
Publicado: (2025)
Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds
por: Li, Shikun, et al.
Publicado: (2023)
por: Li, Shikun, et al.
Publicado: (2023)
Understanding and Enhancing the Transferability of Jailbreaking Attacks
por: Lin, Runqi, et al.
Publicado: (2025)
por: Lin, Runqi, et al.
Publicado: (2025)
Generative Model Inversion Through the Lens of the Manifold Hypothesis
por: Peng, Xiong, et al.
Publicado: (2025)
por: Peng, Xiong, et al.
Publicado: (2025)
MeGU: Machine-Guided Unlearning with Target Feature Disentanglement
por: Wang, Haoyu, et al.
Publicado: (2026)
por: Wang, Haoyu, et al.
Publicado: (2026)
Early Stopping Tabular In-Context Learning
por: Küken, Jaris, et al.
Publicado: (2025)
por: Küken, Jaris, et al.
Publicado: (2025)
Noisy Early Stopping for Noisy Labels
por: Toner, William, et al.
Publicado: (2024)
por: Toner, William, et al.
Publicado: (2024)
Understanding Robust Overfitting from the Feature Generalization Perspective
por: Yu, Chaojian, et al.
Publicado: (2023)
por: Yu, Chaojian, et al.
Publicado: (2023)
What If the Input is Expanded in OOD Detection?
por: Zhang, Boxuan, et al.
Publicado: (2024)
por: Zhang, Boxuan, et al.
Publicado: (2024)
Early Stopping Based on Repeated Significance
por: Bax, Eric, et al.
Publicado: (2024)
por: Bax, Eric, et al.
Publicado: (2024)
MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
por: Tian, Hongduan, et al.
Publicado: (2024)
por: Tian, Hongduan, et al.
Publicado: (2024)
S2O: Early Stopping for Sparse Attention via Online Permutation
por: Zhang, Yu, et al.
Publicado: (2026)
por: Zhang, Yu, et al.
Publicado: (2026)
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning
por: Zhang, Jingfeng, et al.
Publicado: (2023)
por: Zhang, Jingfeng, et al.
Publicado: (2023)
ESPO: Early-Stopping Proximal Policy Optimization
por: Li, Zihang, et al.
Publicado: (2026)
por: Li, Zihang, et al.
Publicado: (2026)
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
por: Cao, Chentao, et al.
Publicado: (2024)
por: Cao, Chentao, et al.
Publicado: (2024)
Instance-dependent Stochastic Lipschitz bandit
por: Potfer, Marius, et al.
Publicado: (2026)
por: Potfer, Marius, et al.
Publicado: (2026)
Mind the Gap Between Prototypes and Images in Cross-domain Finetuning
por: Tian, Hongduan, et al.
Publicado: (2024)
por: Tian, Hongduan, et al.
Publicado: (2024)
Rethinking Early Stopping: Refine, Then Calibrate
por: Berta, Eugène, et al.
Publicado: (2025)
por: Berta, Eugène, et al.
Publicado: (2025)
Statistical Early Stopping for Reasoning Models
por: Xie, Yangxinyu, et al.
Publicado: (2026)
por: Xie, Yangxinyu, et al.
Publicado: (2026)
Negative Label Guided OOD Detection with Pretrained Vision-Language Models
por: Jiang, Xue, et al.
Publicado: (2024)
por: Jiang, Xue, et al.
Publicado: (2024)
Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
por: Wang, Qizhou, et al.
Publicado: (2024)
por: Wang, Qizhou, et al.
Publicado: (2024)
Robust Training of Federated Models with Extremely Label Deficiency
por: Zhang, Yonggang, et al.
Publicado: (2024)
por: Zhang, Yonggang, et al.
Publicado: (2024)
BrokenBind: Universal Modality Exploration beyond Dataset Boundaries
por: Huang, Zhuo, et al.
Publicado: (2026)
por: Huang, Zhuo, et al.
Publicado: (2026)
Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning
por: Huang, Zhuo, et al.
Publicado: (2026)
por: Huang, Zhuo, et al.
Publicado: (2026)
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting
por: Dai, Rong, et al.
Publicado: (2024)
por: Dai, Rong, et al.
Publicado: (2024)
When to Stop Federated Learning: Zero-Shot Generation of Synthetic Validation Data with Generative AI for Early Stopping
por: Lee, Youngjoon, et al.
Publicado: (2025)
por: Lee, Youngjoon, et al.
Publicado: (2025)
Instance-dependent Convergence Theory for Diffusion Models
por: Jiao, Yuchen, et al.
Publicado: (2024)
por: Jiao, Yuchen, et al.
Publicado: (2024)
Convex SGD: Generalization Without Early Stopping
por: Hendrickx, Julien, et al.
Publicado: (2024)
por: Hendrickx, Julien, et al.
Publicado: (2024)
Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
por: Wu, Jingfeng, et al.
Publicado: (2025)
por: Wu, Jingfeng, et al.
Publicado: (2025)
GRADSTOP: Early Stopping of Gradient Descent via Posterior Sampling
por: Jamshidi, Arash, et al.
Publicado: (2025)
por: Jamshidi, Arash, et al.
Publicado: (2025)
Unraveling the Impact of Heterophilic Structures on Graph Positive-Unlabeled Learning
por: Wu, Yuhao, et al.
Publicado: (2024)
por: Wu, Yuhao, et al.
Publicado: (2024)
Few-Shot Adversarial Prompt Learning on Vision-Language Models
por: Zhou, Yiwei, et al.
Publicado: (2024)
por: Zhou, Yiwei, et al.
Publicado: (2024)
Noisy Test-Time Adaptation in Vision-Language Models
por: Cao, Chentao, et al.
Publicado: (2025)
por: Cao, Chentao, et al.
Publicado: (2025)
Ejemplares similares
-
Early Stopping Against Label Noise Without Validation Data
por: Yuan, Suqin, et al.
Publicado: (2025) -
Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
por: Yuan, Suqin, et al.
Publicado: (2025) -
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
por: Lin, Runqi, et al.
Publicado: (2023) -
FORCE: Transferable Visual Jailbreaking Attacks via Feature Over-Reliance CorrEction
por: Lin, Runqi, et al.
Publicado: (2025) -
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
por: Lin, Runqi, et al.
Publicado: (2024)