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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
JMLR
2006
124views more  JMLR 2006»
14 years 9 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
ICIP
2008
IEEE
15 years 11 months ago
Subspace-based methods for image registration and super-resolution
Super-resolution algorithms combine multiple low resolution images into a single high resolution image. They have received a lot of attention recently in various application domai...
Patrick Vandewalle, Loïc Baboulaz, Pier Luigi...
VLDB
2007
ACM
174views Database» more  VLDB 2007»
15 years 10 months ago
An adaptive and dynamic dimensionality reduction method for high-dimensional indexing
Abstract The notorious "dimensionality curse" is a wellknown phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approa...
Heng Tao Shen, Xiaofang Zhou, Aoying Zhou
JMLR
2002
137views more  JMLR 2002»
14 years 9 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller