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133
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WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 6 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
97
Voted
ILP
2001
Springer
15 years 5 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
112
Voted
DSS
2007
127views more  DSS 2007»
15 years 16 days ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
115
Voted
IROS
2006
IEEE
132views Robotics» more  IROS 2006»
15 years 6 months ago
Supervised Learning of Topological Maps using Semantic Information Extracted from Range Data
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
Óscar Martínez Mozos, Wolfram Burgar...
115
Voted
METRICS
1997
IEEE
15 years 4 months ago
Assessing Feedback Of Measurement Data: Relating Schlumberger Rps Practice To Learning Theory
Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...
Rini van Solingen, Egon Berghout, Erik Kooiman