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BMCBI
2011
14 years 4 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
JMLR
2010
108views more  JMLR 2010»
14 years 4 months ago
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
Taiji Suzuki, Masashi Sugiyama
71
Voted
IEICET
2010
132views more  IEICET 2010»
14 years 8 months ago
Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers
Estimating the ratio of two probability density functions (a.k.a. the importance) has recently gathered a great deal of attention since importance estimators can be used for solvi...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, J...
CIKM
2000
Springer
15 years 1 months ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
ICRA
2005
IEEE
102views Robotics» more  ICRA 2005»
15 years 3 months ago
SLAM using Incremental Probabilistic PCA and Dimensionality Reduction
— The recent progress in robot mapping (or SLAM) algorithms has focused on estimating either point features (such as landmarks) or grid-based representations. Both of these repre...
Emma Brunskill, Nicholas Roy