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AAAI
2006
13 years 10 months ago
Learning Representation and Control in Continuous Markov Decision Processes
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
Sridhar Mahadevan, Mauro Maggioni, Kimberly Fergus...
PAMI
2006
117views more  PAMI 2006»
13 years 8 months ago
Metric Learning for Text Documents
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
Guy Lebanon
RSFDGRC
2005
Springer
126views Data Mining» more  RSFDGRC 2005»
14 years 2 months ago
Rough Sets and Higher Order Vagueness
Abstract. We present a rough set approach to vague concept approximation within the adaptive learning framework. In particular, the role of extensions of approximation spaces in se...
Andrzej Skowron, Roman W. Swiniarski
ICPR
2006
IEEE
14 years 9 months ago
Exploiting the Geometry of Gene Expression Patterns for Unsupervised Learning
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Rave Harpaz, Robert M. Haralick
ECCV
2002
Springer
14 years 10 months ago
Learning the Topology of Object Views
A visual representation of an object must meet at least three basic requirements. First, it must allow identification of the object in the presence of slight but unpredictable chan...
Christoph von der Malsburg, Jan Wieghardt, Rolf P....