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CIDM
2009
IEEE
15 years 7 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
PAMI
2011
14 years 7 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
DKE
2007
95views more  DKE 2007»
15 years 15 days ago
Strategies for improving the modeling and interpretability of Bayesian networks
One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can...
Ádamo L. de Santana, Carlos Renato Lisboa F...
CPM
2006
Springer
145views Combinatorics» more  CPM 2006»
15 years 4 months ago
Approximation of RNA Multiple Structural Alignment
Abstract. In the context of non-coding RNA (ncRNA) multiple structural alignment, Davydov and Batzoglou introduced in [7] the problem of finding the largest nested linear graph tha...
Marcin Kubica, Romeo Rizzi, Stéphane Vialet...
UAI
2008
15 years 1 months ago
Observation Subset Selection as Local Compilation of Performance Profiles
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
Yan Radovilsky, Solomon Eyal Shimony