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ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
VTC
2010
IEEE
195views Communications» more  VTC 2010»
13 years 5 months ago
Efficiency of Distributed Compression and Its Dependence on Sensor Node Deployments
Abstract--In this paper we analyze the energy-efficiency of distributed compression and its dependence on the node deployment strategies for Wireless Sensor Networks (WSNs). Reduce...
Frank Oldewurtel, Janne Riihijärvi, Petri M&a...
EDBT
2008
ACM
151views Database» more  EDBT 2008»
14 years 7 months ago
Fast contextual preference scoring of database tuples
To provide users with only relevant data from the huge amount of available information, personalization systems utilize preferences to allow users to express their interest on spe...
Kostas Stefanidis, Evaggelia Pitoura
DCC
2007
IEEE
14 years 7 months ago
Spectral Predictors
Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done usin...
Lorenzo Ibarria, Peter Lindstrom, Jarek Rossignac
PAMI
2011
13 years 2 months ago
Action Recognition Using Mined Hierarchical Compound Features
—The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single frame object recogn...
Andrew Gilbert, John Illingworth, Richard Bowden