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» Termination Analysis with Algorithmic Learning
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FLAIRS
2001
15 years 5 months ago
Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers
Recently we have proposed an algorithm of constructing hierarchical neural network classifiers (HNNC), that is based on a modification of error back-propagation. This algorithm co...
S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju...
157
Voted
ICC
2007
IEEE
217views Communications» more  ICC 2007»
15 years 10 months ago
Decentralized Activation in a ZigBee-enabled Unattended Ground Sensor Network: A Correlated Equilibrium Game Theoretic Analysis
Abstract— We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment i...
Michael Maskery, Vikram Krishnamurthy
127
Voted
ICML
2006
IEEE
16 years 4 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
157
Voted
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 5 months ago
Semi-supervised Feature Selection via Spectral Analysis
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Zheng Zhao, Huan Liu
156
Voted
ECML
2007
Springer
15 years 9 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen