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BMCBI
2008
186views more  BMCBI 2008»
13 years 7 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
SIAMSC
2008
132views more  SIAMSC 2008»
13 years 7 months ago
Stochastic Preconditioning for Diagonally Dominant Matrices
Abstract. This paper presents a new stochastic preconditioning approach for large sparse matrices. For the class of matrices that are row-wise and column-wise irreducibly diagonall...
Haifeng Qian, Sachin S. Sapatnekar
AAAI
1994
13 years 8 months ago
The Automated Mapping of Plans for Plan Recognition
To coordinate with other agents in its environment, an agent needs models of what the other agents are trying to do. When communication is impossible or expensive, this informatio...
Marcus J. Huber, Edmund H. Durfee, Michael P. Well...
AIIA
1997
Springer
13 years 11 months ago
Introducing Abduction into (Extensional) Inductive Logic Programming Systems
We propose an approach for the integration of abduction and induction in Logic Programming. In particular, we show how it is possible to learn an abductive logic program starting f...
Evelina Lamma, Paola Mello, Michela Milano, Fabriz...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 7 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