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ICASSP
2011
IEEE
14 years 10 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 6 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
ICDM
2006
IEEE
100views Data Mining» more  ICDM 2006»
16 years 5 days ago
Meta Clustering
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
IADIS
2009
15 years 3 months ago
Out-of-scene AV data detection
In this paper, we propose a new approach for the automatic audio-based out-of-scene detection of audio-visual data, recorded by different cameras, camcorders or mobile phones duri...
Danil Korchagin
BMCBI
2008
132views more  BMCBI 2008»
15 years 6 months ago
Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of
Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
Raffaele Giancarlo, Davide Scaturro, Filippo Utro