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» A Framework for Multiple-Instance Learning
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KESAMSTA
2009
Springer
14 years 2 months ago
Relational Learning by Imitation
Abstract. Imitative learning can be considered an essential task of humans development. People use instructions and demonstrations provided by other human experts to acquire knowle...
Grazia Bombini, Nicola Di Mauro, Teresa Maria Alto...
FLAIRS
2006
13 years 9 months ago
Dialog Learning in Conversational CBR
Conversational Case-Based Reasoning (CCBR) provides a mixed-initiative dialog for guiding users to refine their problem descriptions incrementally through a question-answering seq...
Mingyang Gu, Agnar Aamodt
CVIU
2008
209views more  CVIU 2008»
13 years 7 months ago
Combining visual dictionary, kernel-based similarity and learning strategy for image category retrieval
This paper presents a search engine architecture, RETIN, aiming at retrieving complex categories in large image databases. For indexing, a scheme based on a two-step quantization ...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...
ICIP
2008
IEEE
14 years 9 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
IJCAI
2003
13 years 9 months ago
Monte Carlo Theory as an Explanation of Bagging and Boosting
In this paper we propose the framework of Monte Carlo algorithms as a useful one to analyze ensemble learning. In particular, this framework allows one to guess when bagging will ...
Roberto Esposito, Lorenza Saitta