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IJAR
2010
130views more  IJAR 2010»
15 years 1 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 9 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
108
Voted
ECCV
2010
Springer
15 years 6 months ago
Binary coherent edge descriptors
Patch descriptors are used for a variety of tasks ranging from finding corresponding points across images, to describing object category parts. In this paper, we propose an image ...
CLEIEJ
2004
168views more  CLEIEJ 2004»
15 years 2 months ago
Contributions of KDD to the Knowledge Management Process: a Case Study
Knowledge Discovery in Databases (KDD), as any organizational process, is carried out beneath a Knowledge Management (KM) model adopted (even informally) by a corporation. KDD is ...
Paulo de Tarso Costa de Sousa, Hércules Ant...
143
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AUTOMATICA
2010
127views more  AUTOMATICA 2010»
15 years 1 months ago
Partitioning datasets based on equalities among parameters
When a phenomenon is described by a parametric model and multiple datasets are available, a key problem in statistics is to discover which datasets are characterized by the same p...
Riccardo Porreca, Giancarlo Ferrari-Trecate