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» A theory of learning from different domains
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NAACL
2010
14 years 7 months ago
Automatic Domain Adaptation for Parsing
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
David McClosky, Eugene Charniak, Mark Johnson
ECML
1993
Springer
15 years 2 months ago
Exploiting Context When Learning to Classify
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the t...
Peter D. Turney
AI
1998
Springer
15 years 2 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih
AAAI
2012
13 years 10 days ago
Transportability of Causal Effects: Completeness Results
The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
Elias Bareinboim, Judea Pearl
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
15 years 3 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose