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ICCBR
1999
Springer
15 years 8 months ago
When Experience Is Wrong: Examining CBR for Changing Tasks and Environments
Case-based problem-solving systems reason and learn from experiences, building up case libraries of problems and solutions to guide future reasoning. The expected bene ts of this l...
David B. Leake, David C. Wilson
CVPR
2012
IEEE
13 years 6 months ago
Unsupervised metric fusion by cross diffusion
Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...
Bo Wang, Jiayan Jiang, Wei Wang 0028, Zhi-Hua Zhou...
ISCC
2003
IEEE
110views Communications» more  ISCC 2003»
15 years 9 months ago
Intelligent Agents Serving Based On The Society Information
In this paper, we propose a serving system consisting intelligent agents processing society information in a multi-user domain. The agents use the similarity information on the us...
Sanem Sariel, B. Tevfik Akgün
EWCBR
2008
Springer
15 years 6 months ago
Discovering Feature Weights for Feature-based Indexing of Q-tables
In this paper we propose an approach to address the old problem of identifying the feature conditions under which a gaming strategy can be effective. For doing this, we will build ...
Chad Hogg, Stephen Lee-Urban, Bryan Auslander, H&e...
ECAI
2008
Springer
15 years 6 months ago
Multilingual Evidence Improves Clustering-based Taxonomy Extraction
We present a system for taxonomy extraction, aimed at providing a taxonomic backbone in an ontology learning environment. We follow previous research in using hierarchical clusteri...
Hans Hjelm, Paul Buitelaar