1 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees
Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano
The statistical characteristics of instance-label pairs often change with time in practical scenarios of supervised classification. Conventional learning techniques adapt to such c…
Minimax Classification with 0-1 Loss and Performance Guarantees
Santiago Mazuelas, Andrea Zanoni, Aritz Perez
Supervised classification techniques use training samples to find classification rules with small expected 0-1 loss. Conventional methods achieve efficient learning and out-of-samp…
Supervised classification via minimax probabilistic transformations
Santiago Mazuelas, Andrea Zanoni, Aritz Perez
Conventional techniques for supervised classification constrain the classification rules considered and use surrogate losses for classification 0-1 loss. Favored families of classi…
General Supervision via Probabilistic Transformations
Santiago Mazuelas, Aritz Perez
Different types of training data have led to numerous schemes for supervised classification. Current learning techniques are tailored to one specific scheme and cannot handle gener…