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Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
The statistical characteristics of instance-label pairs often change with time in practical scenarios of supervised classification. Conventional learning techniques adapt to such concept drift accounting for a scalar rate ...
Probabilistic Load Forecasting Based on Adaptive Online Learning
Load forecasting is crucial for multiple energy management tasks such as scheduling generation capacity, planning supply and demand, and minimizing energy trade costs. Such relevance has increased even more in recent ...