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ICML
2009
IEEE
14 years 9 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
BMCBI
2006
111views more  BMCBI 2006»
13 years 8 months ago
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
Background: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples...
Tomer Hertz, Chen Yanover
ICML
2010
IEEE
13 years 9 months ago
Application of Machine Learning To Epileptic Seizure Detection
We present and evaluate a machine learning approach to constructing patient-specific classifiers that detect the onset of an epileptic seizure through analysis of the scalp EEG, a...
Ali H. Shoeb, John V. Guttag
JMLR
2010
230views more  JMLR 2010»
13 years 3 months ago
Learning Dissimilarities for Categorical Symbols
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
Jierui Xie, Boleslaw K. Szymanski, Mohammed J. Zak...
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
14 years 2 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...