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ECAI
2004
Springer
16 years 8 days ago
Avatars That Learn How to Behave
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Adam Szarowicz, Paolo Remagnino
IJAR
2006
89views more  IJAR 2006»
15 years 6 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
PR
2007
139views more  PR 2007»
15 years 6 months ago
Learning the kernel matrix by maximizing a KFD-based class separability criterion
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
Dit-Yan Yeung, Hong Chang, Guang Dai
ROMAN
2007
IEEE
150views Robotics» more  ROMAN 2007»
16 years 1 months ago
Asymmetric Interpretations of Positive and Negative Human Feedback for a Social Learning Agent
— The ability for people to interact with robots and teach them new skills will be crucial to the successful application of robots in everyday human environments. In order to des...
Andrea Lockerd Thomaz, Cynthia Breazeal
CIARP
2008
Springer
15 years 9 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...