6 citations · 7 across the 3 of their papers we have counts for
3 papers
MuRAL-CPD: Active Learning for Multiresolution Change Point Detection
Stefano Bertolasi, Diego Carrera, Diego Stucchi +2
Change Point Detection (CPD) is a critical task in time series analysis, aiming to identify moments when the underlying data-generating process shifts. Traditional CPD methods ofte…
Change Detection in Multivariate data streams: Online Analysis with Kernel-QuantTree
Michelangelo Olmo Nogara Notarianni, Filippo Leveni, Diego Stucchi +2
We present Kernel-QuantTree Exponentially Weighted Moving Average (KQT-EWMA), a non-parametric change-detection algorithm that combines the Kernel-QuantTree (KQT) histogram and the…
Class Distribution Monitoring for Concept Drift Detection
Diego Stucchi, Luca Frittoli, Giacomo Boracchi
We introduce Class Distribution Monitoring (CDM), an effective concept-drift detection scheme that monitors the class-conditional distributions of a datastream. In particular, our…