128 citations · 293 across the 39 of their papers we have counts for
9 papers · 1 filter
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model Selection
Luca Magri, Filippo Leveni, Giacomo Boracchi
We address the problem of recovering multiple structures of different classes in a dataset contaminated by noise and outliers. In particular, we consider geometric structures defin…
Hashing for Structure-based Anomaly Detection
Filippo Leveni, Luca Magri, Cesare Alippi +1
We focus on the problem of identifying samples in a set that do not conform to structured patterns represented by low-dimensional manifolds. An effective way to solve this problem…
PIF: Anomaly detection via preference embedding
Filippo Leveni, Luca Magri, Giacomo Boracchi +1
We address the problem of detecting anomalies with respect to structured patterns. To this end, we conceive a novel anomaly detection method called PIF, that combines the advantage…
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer +2
The anomaly detection literature is abundant with offline methods, which require repeated access to data in memory, and impose impractical assumptions when applied to a streaming c…
Preference Isolation Forest for Structure-based Anomaly Detection
Filippo Leveni, Luca Magri, Cesare Alippi +1
We address the problem of detecting anomalies as samples that do not conform to structured patterns represented by low-dimensional manifolds. To this end, we conceive a general ano…
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…
Nonparametric and Online Change Detection in Multivariate Datastreams using QuantTree
Luca Frittoli, Diego Carrera, Giacomo Boracchi
We address the problem of online change detection in multivariate datastreams, and we introduce QuantTree Exponentially Weighted Moving Average (QT-EWMA), a nonparametric change-de…
Adversarial Scratches: Deployable Attacks to CNN Classifiers
Loris Giulivi, Malhar Jere, Loris Rossi +4
A growing body of work has shown that deep neural networks are susceptible to adversarial examples. These take the form of small perturbations applied to the model's input which le…