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JMLR
2006
103views more  JMLR 2006»
13 years 11 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev
APIN
2008
110views more  APIN 2008»
13 years 11 months ago
Explaining inferences in Bayesian networks
While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall sh...
Ghim-Eng Yap, Ah-Hwee Tan, HweeHwa Pang
PERCOM
2004
ACM
14 years 10 months ago
Learning to Detect User Activity and Availability from a Variety of Sensor Data
Using a networked infrastructure of easily available sensors and context-processing components, we are developing applications for the support of workplace interactions. Notions o...
Dave Snowdon, Jean-Luc Meunier, Martin Mühlen...
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 11 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 11 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto