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108
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ICML
2008
IEEE
16 years 2 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
ICML
2009
IEEE
15 years 8 months ago
Decision tree and instance-based learning for label ranking
The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...
Weiwei Cheng, Jens C. Huhn, Eyke Hüllermeier
AIME
2007
Springer
15 years 8 months ago
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data
Abstract. The practice of medicine is becoming increasingly evidencebased and clinical practice guidelines (CPGs) are necessary for advancing evidence-based medicine (EBM). We hypo...
Subramani Mani, Constantin F. Aliferis
80
Voted
ECML
2001
Springer
15 years 6 months ago
Comparing the Bayes and Typicalness Frameworks
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
Thomas Melluish, Craig Saunders, Ilia Nouretdinov,...
BMCBI
2006
118views more  BMCBI 2006»
15 years 2 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...