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ICRA
2007
IEEE
134views Robotics» more  ICRA 2007»
13 years 11 months ago
Towards a Real-Time Bayesian Imitation System for a Humanoid Robot
Abstract— Imitation learning, or programming by demonstration (PbD), holds the promise of allowing robots to acquire skills from humans with domain-specific knowledge, who nonet...
Aaron P. Shon, Joshua J. Storz, Rajesh P. N. Rao
IROS
2008
IEEE
144views Robotics» more  IROS 2008»
13 years 11 months ago
Learning nonparametric policies by imitation
— A long cherished goal in artificial intelligence has been the ability to endow a robot with the capacity to learn and generalize skills from watching a human teacher. Such an ...
David B. Grimes, Rajesh P. N. Rao
TSP
2008
167views more  TSP 2008»
13 years 3 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
NIPS
2003
13 years 6 months ago
Probabilistic Inference in Human Sensorimotor Processing
When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
Konrad P. Körding, Daniel M. Wolpert
CVPR
2004
IEEE
14 years 6 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black