Handling concept drift via model reuse

DOI10.1007/s10994-019-05835-wzbMath1494.68237arXiv1809.02804OpenAlexW2979827629WikidataQ126862529 ScholiaQ126862529MaRDI QIDQ2183593

Peng Zhao, Zhi-Hua Zhou, Le-Wen Cai

Publication date: 27 May 2020

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1809.02804

zbMATH Keywords

concept driftmodel reusenon-stationary environments

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Statistical aspects of big data and data science (62R07) Computational aspects of data analysis and big data (68T09)

Related Items (1)

Partially observable environment estimation with uplift inference for reinforcement learning based recommendation

Uses Software

• AdaBoost.MH

Cites Work

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• Oracle inequalities in empirical risk minimization and sparse recovery problems. École d'Été de Probabilités de Saint-Flour XXXVIII-2008.
• Tracking drifting concepts by minimizing disagreements
• Fast rates by transferring from auxiliary hypotheses
• Local Rademacher complexities
• Non-Stationary Stochastic Optimization
• A Vector-Contraction Inequality for Rademacher Complexities
• New Analysis and Algorithm for Learning with Drifting Distributions
• How to use expert advice
• 10.1162/153244303321897690
• A survey on concept drift adaptation
• Prediction, Learning, and Games

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