Imagen de Portada

Adaptive Estimation and Learning under Temporal Distribution Shift

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Baby, Dheeraj, Tang, Yifei, Nguyen, Hieu Duy, Wang, Yu-Xiang, Pyati, Rohit
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach
por: Baby, Dheeraj, et al.
Publicado: (2025)

Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
por: Wu, Ruihan, et al.
Publicado: (2024)

Online Matrix Completion: A Collaborative Approach with Hott Items
por: Baby, Dheeraj, et al.
Publicado: (2024)

When In-Distribution Gains Fail: Evaluating Weak-to-Strong Reward Models under Preference Shift
por: Le, Khoi, et al.
Publicado: (2026)

Cost-Adaptive Recourse Recommendation by Adaptive Preference Elicitation
por: Nguyen, Duy, et al.
Publicado: (2024)

Optimal Empirical Risk Minimization under Temporal Distribution Shifts
por: Jeong, Yujin, et al.
Publicado: (2025)

Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift
por: Park, Heewon, et al.
Publicado: (2026)

Cold-start Recommendation by Personalized Embedding Region Elicitation
por: Nguyen, Hieu Trung, et al.
Publicado: (2024)

Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift
por: Xie, Renchunzi, et al.
Publicado: (2024)

Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder
por: Nguyen, Duy A., et al.
Publicado: (2023)

Trustworthy Machine Learning under Distribution Shifts
por: Huang, Zhuo
Publicado: (2025)

Robust Uncertainty Estimation under Distribution Shift via Difference Reconstruction
por: Xu, Xinran, et al.
Publicado: (2026)

Training-Conditional Coverage Bounds under Covariate Shift
por: Pournaderi, Mehrdad, et al.
Publicado: (2024)

ODD: Overlap-aware Estimation of Model Performance under Distribution Shift
por: Mishra, Aayush, et al.
Publicado: (2025)

OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
por: Li, Lin, et al.
Publicado: (2023)

CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift
por: Nguyen, Anh T, et al.
Publicado: (2023)

Graph Fairness Learning under Distribution Shifts
por: Li, Yibo, et al.
Publicado: (2024)

Bias as a Virtue: Rethinking Generalization under Distribution Shifts
por: Chen, Ruixuan, et al.
Publicado: (2025)

Federated Learning with Profile Mapping under Distribution Shifts and Drifts
por: Li, Mohan, et al.
Publicado: (2026)

Graphs Generalization under Distribution Shifts
por: Tian, Qin, et al.
Publicado: (2024)

Conformalized Signal Temporal Logic Inference under Covariate Shift
por: Wang, Yixuan, et al.
Publicado: (2026)

Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
por: Xue, Yihao, et al.
Publicado: (2023)

Generative Conditional Distributions by Neural (Entropic) Optimal Transport
por: Nguyen, Bao, et al.
Publicado: (2024)

Model Assessment and Selection under Temporal Distribution Shift
por: Han, Elise, et al.
Publicado: (2024)

ShiftKD: Benchmarking Knowledge Distillation under Distribution Shift
por: Zhang, Songming, et al.
Publicado: (2023)

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
por: Zhang, Zeyang, et al.
Publicado: (2024)

Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts
por: Jiang, Haiyang, et al.
Publicado: (2024)

Adaptive Two-Phase Finetuning LLMs for Japanese Legal Text Retrieval
por: Trung, Quang Hoang, et al.
Publicado: (2024)

Tracking Adaptation Time: Metrics for Temporal Distribution Shift
por: Iovine, Lorenzo, et al.
Publicado: (2026)

Distributionally Robust Coreset Selection under Covariate Shift
por: Tanaka, Tomonari, et al.
Publicado: (2025)

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift
por: Lim, Sungjun, et al.
Publicado: (2026)

Mean-Variance Portfolio Selection in Long-Term Investments with Unknown Distribution: Online Estimation, Risk Aversion under Ambiguity, and Universality of Algorithms
por: Lam, Duy Khanh
Publicado: (2024)

Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts
por: Bui, Ha Manh, et al.
Publicado: (2024)

Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
por: Bui, Ha Manh, et al.
Publicado: (2023)

ASAP: Unsupervised Post-training with Label Distribution Shift Adaptive Learning Rate
por: Park, Heewon, et al.
Publicado: (2025)

Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
por: Qiao, Dan, et al.
Publicado: (2024)

Distributional Surgery for Language Model Activations
por: Nguyen, Bao, et al.
Publicado: (2025)

Optimal Classification under Performative Distribution Shift
por: Cyffers, Edwige, et al.
Publicado: (2024)

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing
por: Guo, Yongxin, et al.
Publicado: (2024)

Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards
por: Nguyen, Hieu Trung, et al.
Publicado: (2026)