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FOCM
2006
65views more  FOCM 2006»
15 years 4 months ago
Approximation Methods for Supervised Learning
Let be an unknown Borel measure defined on the space Z := X
Ronald A. DeVore, Gerard Kerkyacharian, Dominique ...
CVPR
2005
IEEE
16 years 6 months ago
Learning to Track: Conceptual Manifold Map for Closed-Form Tracking
Our objective is to model the visual manifold of object appearance corresponding to geometric transformation. We learn a generative model for object appearance where the appearanc...
Ahmed M. Elgammal
ABIALS
2008
Springer
15 years 11 months ago
A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion
Abstract. We present a model of motor learning based on a combination of Operational Space Control and Optimal Control. Anticipatory processes are used both in the learning of the ...
Camille Salaün, Vincent Padois, Olivier Sigau...
AAAI
2008
15 years 7 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley
IJCAI
1989
15 years 5 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter