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» Spectral Methods for Automatic Multiscale Data Clustering
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FTML
2010
159views more  FTML 2010»
13 years 6 months ago
Dimension Reduction: A Guided Tour
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
Christopher J. C. Burges
ICASSP
2011
IEEE
12 years 11 months ago
Joint modeling of observed inter-arrival times and waveform data with multiple hidden states for neural spike-sorting
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Brett Matthews, Mark Clements
ICMCS
2006
IEEE
180views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Automatic Speaker Segmentation using Multiple Features and Distance Measures: A Comparison of Three Approaches
This paper addresses the problem of unsupervised speaker change detection. Three systems based on the Bayesian Information Criterion (BIC) are tested. The first system investigat...
Margarita Kotti, Luis P. M. Martins, Emmanouil Ben...
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 1 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
SAC
2009
ACM
14 years 2 months ago
Parameterless outlier detection in data streams
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
Alice Marascu, Florent Masseglia