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» A theory of learning from different domains
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AAAI
2012
13 years 10 days ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
AI
2011
Springer
14 years 5 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
IRI
2003
IEEE
15 years 3 months ago
Generalizing Interface Design Knowledge: Lessons Learned from Developing a Claims Library
The experience of preparing interface design knowledge to be reusable allows reflection on the process, potential, and general challenges of effectively and efficiently using this...
Catherine Payne, C. F. Allgood, Christa M. Chewar,...
ILP
2004
Springer
15 years 3 months ago
Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. Our research has focused on Information Extraction (IE), a task that typically invol...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
15 years 3 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...