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ICML
2007
IEEE
16 years 4 months ago
Asymptotic Bayesian generalization error when training and test distributions are different
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
Keisuke Yamazaki, Klaus-Robert Müller, Masash...
169
Voted
ILP
2007
Springer
15 years 9 months ago
Learning to Assign Degrees of Belief in Relational Domains
A recurrent question in the design of intelligent agents is how to assign degrees of beliefs, or subjective probabilities, to various events in a relational environment. In the sta...
Frédéric Koriche
ICCV
2005
IEEE
15 years 9 months ago
Learning Effective Image Metrics from Few Pairwise Examples
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...
Hwann-Tzong Chen, Tyng-Luh Liu, Chiou-Shann Fuh
ECAL
2003
Springer
15 years 8 months ago
The Learning and Emergence of Mildly Context Sensitive Languages
This paper describes a framework for studies of the adaptive acquisition and evolution of language, with the following components: language learning begins by associating words wit...
Edward P. Stabler, Travis C. Collier, Gregory M. K...
156
Voted
AMDO
2006
Springer
15 years 7 months ago
Human Motion Synthesis by Motion Manifold Learning and Motion Primitive Segmentation
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
Chan-Su Lee, Ahmed M. Elgammal