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» Learning from Highly Structured Data by Decomposition
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ICML
2005
IEEE
15 years 10 months ago
A causal approach to hierarchical decomposition of factored MDPs
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...
Anders Jonsson, Andrew G. Barto
92
Voted
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
14 years 11 months ago
MACH: Fast Randomized Tensor Decompositions
Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer visio...
Charalampos E. Tsourakakis
ECML
1997
Springer
15 years 1 months ago
Constructing Intermediate Concepts by Decomposition of Real Functions
In learning from examples it is often useful to expand an attribute-vector representation by intermediate concepts. The usual advantage of such structuring of the learning problemi...
Janez Demsar, Blaz Zupan, Marko Bohanec, Ivan Brat...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
15 years 4 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
82
Voted
ICDE
2010
IEEE
273views Database» more  ICDE 2010»
15 years 9 months ago
WikiAnalytics: Ad-hoc Querying of Highly Heterogeneous Structured Data
Searching and extracting meaningful information out of highly heterogeneous datasets is a hot topic that received a lot of attention. However, the existing solutions are based on e...
Andrey Balmin, Emiran Curtmola