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ECCV
2010
Springer
15 years 7 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
CIARP
2008
Springer
15 years 7 months ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
IJAR
2006
89views more  IJAR 2006»
15 years 5 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
196
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PKAW
2010
15 years 3 months ago
MMG: A Learning Game Platform for Understanding and Predicting Human Recall Memory
How humans infer probable information from the limited observed data? How they are able to build on little knowledge about the context in hand? Is the human memory repeatedly const...
Umer Fareed, Byoung-Tak Zhang
ISAMI
2010
14 years 12 months ago
Ontology and SWRL-Based Learning Model for Home Automation Controlling
Abstract. In the present paper we describe IntelliDomo's learning model, an ontology-based expert system able to control a home automation system and to learn user's beha...
Pablo A. Valiente-Rocha, Adolfo Lozano Tello