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» A Piecewise Linear Network Classifier
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SENSYS
2006
ACM
14 years 1 months ago
Target tracking with binary proximity sensors: fundamental limits, minimal descriptions, and algorithms
We explore fundamental performance limits of tracking a target in a two-dimensional field of binary proximity sensors, and design algorithms that attain those limits. In particul...
Nisheeth Shrivastava, Raghuraman Mudumbai, Upamany...
MLDM
2007
Springer
14 years 1 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...
BMCBI
2006
143views more  BMCBI 2006»
13 years 7 months ago
IsoSVM - Distinguishing isoforms and paralogs on the protein level
Background: Recent progress in cDNA and EST sequencing is yielding a deluge of sequence data. Like database search results and proteome databases, this data gives rise to inferred...
Michael Spitzer, Stefan Lorkowski, Paul Cullen, Al...
IJCNN
2006
IEEE
14 years 1 months ago
Echo State Networks for Determining Harmonic Contributions from Nonlinear Loads
—This paper investigates the application of a new kind of recurrent neural network called Echo State Networks (ESNs) for the problem of measuring the actual amount of harmonic cu...
Joy Mazumdar, Ganesh K. Venayagamoorthy, Ronald G....
CVPR
1999
IEEE
14 years 9 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...