Search Results - "Angiulli, Fabrizio"

Uncertain distance-based outlier detection with arbitrarily shaped data objects by Angiulli, Fabrizio, Fassetti, Fabio

“…Enabling information systems to face anomalies in the presence of uncertainty is a compelling and challenging task. In this work the problem of unsupervised…”
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Distance-based outlier queries in data streams: the novel task and algorithms by Angiulli, Fabrizio, Fassetti, Fabio

“…This work proposes a method for detecting distance-based outliers in data streams under the sliding window model. The novel notion of one-time outlier query is…”
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LatentOut: an unsupervised deep anomaly detection approach exploiting latent space distribution by Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca

“…Anomaly detection methods exploiting autoencoders (AE) have shown good performances. Unfortunately, deep non-linear architectures are able to perform high…”
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{{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution by Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca

“…Abstract Anomaly detection methods exploiting autoencoders (AE) have shown good performances. Unfortunately, deep non-linear architectures are able to perform…”
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Anomaly detection with correlation laws by Angiulli, Fabrizio, Fassetti, Fabio, Serrao, Cristina

“…Datasets from different domains usually contain data defined over a wide set of attributes among which various degrees of correlation exist. The identification…”
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Pruning strategies for nearest neighbor competence preservation learners by Angiulli, Fabrizio, Narvaez, Estela

“…In order to alleviate both the spatial and temporal cost of the nearest neighbor classification rule, competence preservation techniques aim at substituting…”
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Enhancing anomaly detectors with LatentOut by Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca

“…Latent Out is a recently introduced algorithm for unsupervised anomaly detection which enhances latent space-based neural methods, namely ( Variational )…”
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Prototype-Based Domain Description for One-Class Classification by Angiulli, F.

“…This work introduces the Prototype-based Domain Description rule (PDD) one-class classifier. PDD is a nearest neighbor-based classifier since it accepts…”
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Explaining outliers and anomalous groups via subspace density contrastive loss by Angiulli, Fabrizio, Fassetti, Fabio, Nisticò, Simona, Palopoli, Luigi

“…Explainable AI refers to techniques by which the reasons underlying decisions taken by intelligent artifacts are single out and provided to users. Outlier…”
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Indexing Uncertain Data in General Metric Spaces by Angiulli, Fabrizio, Fassetti, Fabio

“…In this study, we deal with the problem of efficiently answering range queries over uncertain objects in a general metric space. In this study, an uncertain…”
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Graph-based construction of minimal models by Angiulli, Fabrizio, Ben-Eliyahu-Zohary, Rachel, Fassetti, Fabio, Palopoli, Luigi

“…Reasoning with minimal models is at the heart of many knowledge representation systems. Yet, it turns out that this task is formidable even when very simple…”
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Reducing distance computations for distance-based outliers by Angiulli, Fabrizio, Basta, Stefano, Lodi, Stefano, Sartori, Claudio

“…•The paper introduces the FastSolvingSet algorithm to discover outliers.•This algorithm computes the distance based outliers with no approximation.•The…”
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Fast Nearest Neighbor Condensation for Large Data Sets Classification by Angiulli, F.

“…This work has two main objectives, namely, to introduce a novel algorithm, called the fast condensed nearest neighbor (FCNN) rule, for computing a…”
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Exploiting domain knowledge to detect outliers by Angiulli, Fabrizio, Fassetti, Fabio

“…We present a novel definition of outlier whose aim is to embed an available domain knowledge in the process of discovering outliers. Specifically, given a…”
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Guest Editorial: Non-IID Outlier Detection in Complex Contexts by Pang, Guansong, Angiulli, Fabrizio, Cucuringu, Mihai, Liu, Huan

“…Outlier detection, also known as anomaly detection, aims at identifying data instances that are rare or significantly different from the majority of instances…”
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A density estimation approach for detecting and explaining exceptional values in categorical data by Angiulli, Fabrizio, Fassetti, Fabio, Palopoli, Luigi, Serrao, Cristina

“…In this work we deal with the problem of detecting and explaining anomalous values in categorical datasets. We take the perspective of perceiving an attribute…”
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GPU Strategies for Distance-Based Outlier Detection by Angiulli, Fabrizio, Basta, Stefano, Lodi, Stefano, Sartori, Claudio

“…The process of discovering interesting patterns in large, possibly huge, data sets is referred to as data mining, and can be performed in several flavours,…”
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Outlying property detection with numerical attributes by Angiulli, Fabrizio, Fassetti, Fabio, Manco, Giuseppe, Palopoli, Luigi

“…The outlying property detection problem (OPDP) is the problem of discovering the properties distinguishing a given object, known in advance to be an outlier in…”
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Discovering Characterizations of the Behavior of Anomalous Subpopulations by Angiulli, Fabrizio, Fassetti, Fabio, Palopoli, Luigi

“…We consider the problem of discovering attributes, or properties, accounting for the a priori stated abnormality of a group of anomalous individuals (the…”
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Mining sponge phenomena in RNA expression data by Angiulli, Fabrizio, Colombo, Teresa, Fassetti, Fabio, Furfaro, Angelo, Paci, Paola

“…In the last few years, the interactions among competing endogenous RNAs (ceRNAs) have been recognized as a key post-transcriptional regulatory mechanism in…”
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