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CIDM
2009
IEEE
14 years 4 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...
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
13 years 8 months ago
Learning Algorithms for Link Prediction Based on Chance Constraints
In this paper, we consider the link prediction problem, where we are given a partial snapshot of a network at some time and the goal is to predict the additional links formed at a ...
Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lis...
AAAI
2008
14 years 11 days ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
HIS
2008
13 years 11 months ago
Towards a Highly Scalable Hybrid Metaheuristic for Haplotype Inference Under Parsimony
Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This ...
Stefano Benedettini, Luca Di Gaspero, Andrea Roli
UAI
2008
13 years 11 months ago
Improving the Accuracy and Efficiency of MAP Inference for Markov Logic
In this work we present Cutting Plane Inference (CPI), a Maximum A Posteriori (MAP) inference method for Statistical Relational Learning. Framed in terms of Markov Logic and inspi...
Sebastian Riedel