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DAWAK
2006
Springer
13 years 11 months ago
Learning Classifiers from Distributed, Ontology-Extended Data Sources
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
ASAP
2010
IEEE
143views Hardware» more  ASAP 2010»
13 years 9 months ago
Loop transformations for interface-based hierarchies IN SDF graphs
Data-flow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of data-flow, termed synchronous data...
Jonathan Piat, Shuvra S. Bhattacharyya, Mickaë...
IJCAI
2003
13 years 8 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
MP
1998
109views more  MP 1998»
13 years 7 months ago
Rounding algorithms for covering problems
In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...
Dimitris Bertsimas, Rakesh V. Vohra
IJAR
2011
86views more  IJAR 2011»
12 years 10 months ago
On open questions in the geometric approach to structural learning Bayesian nets
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
Milan Studený, Jirí Vomlel