Guardado en:
| Autor principal: | Zaichyk, Sofiya |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2512.13506 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Semantic Fusion: Verifiable Alignment in Decentralized Multi-Agent Systems
por: Zaichyk, Sofiya
Publicado: (2026)
por: Zaichyk, Sofiya
Publicado: (2026)
Prequential posteriors
por: Sinha-Roy, Shreya, et al.
Publicado: (2025)
por: Sinha-Roy, Shreya, et al.
Publicado: (2025)
Distributionally Robust Policy Learning under Concept Drifts
por: Wang, Jingyuan, et al.
Publicado: (2024)
por: Wang, Jingyuan, et al.
Publicado: (2024)
Federated Learning with Profile Mapping under Distribution Shifts and Drifts
por: Li, Mohan, et al.
Publicado: (2026)
por: Li, Mohan, et al.
Publicado: (2026)
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift
por: Chen, Junbao, et al.
Publicado: (2024)
por: Chen, Junbao, et al.
Publicado: (2024)
An Improved Algorithm for Learning Drifting Discrete Distributions
por: Mazzetto, Alessio
Publicado: (2024)
por: Mazzetto, Alessio
Publicado: (2024)
Distribution-Free Predictive Inference under Unknown Temporal Drift
por: Han, Elise, et al.
Publicado: (2024)
por: Han, Elise, et al.
Publicado: (2024)
Distributionally Robust Federated Learning with Client Drift Minimization
por: Krouka, Mounssif, et al.
Publicado: (2025)
por: Krouka, Mounssif, et al.
Publicado: (2025)
Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift
por: Beytur, Hasan Burhan, et al.
Publicado: (2025)
por: Beytur, Hasan Burhan, et al.
Publicado: (2025)
Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control
por: Zamzmi, Ghada, et al.
Publicado: (2024)
por: Zamzmi, Ghada, et al.
Publicado: (2024)
Online Regularized Statistical Learning in Reproducing Kernel Hilbert Space With Non-Stationary Data
por: Zhang, Xiwei, et al.
Publicado: (2024)
por: Zhang, Xiwei, et al.
Publicado: (2024)
Statistical Quality and Reproducibility of Pseudorandom Number Generators in Machine Learning technologies
por: Antunes, Benjamin A.
Publicado: (2025)
por: Antunes, Benjamin A.
Publicado: (2025)
RCCDA: Adaptive Model Updates in the Presence of Concept Drift under a Constrained Resource Budget
por: Piaseczny, Adam, et al.
Publicado: (2025)
por: Piaseczny, Adam, et al.
Publicado: (2025)
Testing properties of trees in graphical models with covariance queries
por: Burova, Sofiya, et al.
Publicado: (2026)
por: Burova, Sofiya, et al.
Publicado: (2026)
DriftGuard: Mitigating Asynchronous Data Drift in Federated Learning
por: Han, Yizhou, et al.
Publicado: (2026)
por: Han, Yizhou, et al.
Publicado: (2026)
Privacy-Preserving Personalized Federated Learning for Distributed Photovoltaic Disaggregation under Statistical Heterogeneity
por: Chen, Xiaolu, et al.
Publicado: (2025)
por: Chen, Xiaolu, et al.
Publicado: (2025)
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
por: McFadden, Shae, et al.
Publicado: (2025)
por: McFadden, Shae, et al.
Publicado: (2025)
Online Boosting Adaptive Learning under Concept Drift for Multistream Classification
por: Yu, En, et al.
Publicado: (2023)
por: Yu, En, et al.
Publicado: (2023)
One-Step Sampler for Boltzmann Distributions via Drifting
por: Cao, Wenhan, et al.
Publicado: (2026)
por: Cao, Wenhan, et al.
Publicado: (2026)
Statistical Learning Theory for Distributional Classification
por: Fiedler, Christian
Publicado: (2026)
por: Fiedler, Christian
Publicado: (2026)
An Information-Theoretic Analysis for Federated Learning under Concept Drift
por: Peng, Fu, et al.
Publicado: (2025)
por: Peng, Fu, et al.
Publicado: (2025)
A Statistical Analysis of Deep Federated Learning for Intrinsically Low-dimensional Data
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
GUIrilla: A Scalable Framework for Automated Desktop UI Exploration
por: Garkot, Sofiya, et al.
Publicado: (2025)
por: Garkot, Sofiya, et al.
Publicado: (2025)
Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning
por: Xie, Yiling, et al.
Publicado: (2023)
por: Xie, Yiling, et al.
Publicado: (2023)
A Statistical Analysis for Supervised Deep Learning with Exponential Families for Intrinsically Low-dimensional Data
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
Generalized Incremental Learning under Concept Drift across Evolving Data Streams
por: Yu, En, et al.
Publicado: (2025)
por: Yu, En, et al.
Publicado: (2025)
Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
por: Sun, Ke, et al.
Publicado: (2021)
por: Sun, Ke, et al.
Publicado: (2021)
Drift Q-Learning
por: Houssaini, Anas, et al.
Publicado: (2026)
por: Houssaini, Anas, et al.
Publicado: (2026)
Optimized Deep Learning Models for Malware Detection under Concept Drift
por: Maillet, William, et al.
Publicado: (2023)
por: Maillet, William, et al.
Publicado: (2023)
Stress-Aware Learning under KL Drift via Trust-Decayed Mirror Descent
por: Raj, Gabriel Nixon
Publicado: (2025)
por: Raj, Gabriel Nixon
Publicado: (2025)
Keep Rehearsing and Refining: Lifelong Learning Vehicle Routing under Continually Drifting Tasks
por: Pei, Jiyuan, et al.
Publicado: (2026)
por: Pei, Jiyuan, et al.
Publicado: (2026)
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
A Reproducibility Analysis of PO4ISR: Diagnosing and Mitigating Semantic Drift in LLM-Based Session Recommendation
por: Tiwari, Aditya, et al.
Publicado: (2026)
por: Tiwari, Aditya, et al.
Publicado: (2026)
UPRPRC: Unified Pipeline for Reproducing Parallel Resources -- Corpus from the United Nations
por: Lu, Qiuyang, et al.
Publicado: (2025)
por: Lu, Qiuyang, et al.
Publicado: (2025)
Overcoming Domain Drift in Online Continual Learning
por: Lyu, Fan, et al.
Publicado: (2024)
por: Lyu, Fan, et al.
Publicado: (2024)
Benchmarking Machine Learning Models for IoT Malware Detection under Data Scarcity and Drift
por: Lyon, Jake, et al.
Publicado: (2026)
por: Lyon, Jake, et al.
Publicado: (2026)
Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks
por: Vaquet, Valerie, et al.
Publicado: (2024)
por: Vaquet, Valerie, et al.
Publicado: (2024)
An Adaptive Sampling Framework for Detecting Localized Concept Drift under Label Scarcity
por: Pyeon, Junghee, et al.
Publicado: (2025)
por: Pyeon, Junghee, et al.
Publicado: (2025)
Distributional Random Forests for Complex Survey Designs on Reproducing Kernel Hilbert Spaces
por: Zou, Yating, et al.
Publicado: (2025)
por: Zou, Yating, et al.
Publicado: (2025)
On the Intrinsic Dimensions of Data in Kernel Learning
por: Takhanov, Rustem
Publicado: (2026)
por: Takhanov, Rustem
Publicado: (2026)
Ejemplares similares
-
Semantic Fusion: Verifiable Alignment in Decentralized Multi-Agent Systems
por: Zaichyk, Sofiya
Publicado: (2026) -
Prequential posteriors
por: Sinha-Roy, Shreya, et al.
Publicado: (2025) -
Distributionally Robust Policy Learning under Concept Drifts
por: Wang, Jingyuan, et al.
Publicado: (2024) -
Federated Learning with Profile Mapping under Distribution Shifts and Drifts
por: Li, Mohan, et al.
Publicado: (2026) -
Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift
por: Chen, Junbao, et al.
Publicado: (2024)