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NN
2006
Springer
127views Neural Networks» more  NN 2006»
13 years 9 months ago
The asymptotic equipartition property in reinforcement learning and its relation to return maximization
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
Kazunori Iwata, Kazushi Ikeda, Hideaki Sakai
CVPR
2009
IEEE
15 years 5 months ago
Learning sign language by watching TV (using weakly aligned subtitles)
The goal of this work is to automatically learn a large number of British Sign Language (BSL) signs from TV broadcasts. We achieve this by using the supervisory information avai...
Patrick Buehler (University of Oxford), Mark Everi...
ICCV
2005
IEEE
14 years 11 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
COLT
1999
Springer
14 years 2 months ago
Uniform-Distribution Attribute Noise Learnability
We study the problem of PAC-learning Boolean functions with random attribute noise under the uniform distribution. We define a noisy distance measure for function classes and sho...
Nader H. Bshouty, Jeffrey C. Jackson, Christino Ta...
RAS
2006
91views more  RAS 2006»
13 years 9 months ago
Visual navigation and obstacle avoidance using a steering potential function
Humans have a remarkable ability to navigate using only vision, but mobile robots have not been nearly as successful. We propose a new approach to vision-guided local navigation, ...
Wesley H. Huang, Brett R. Fajen, Jonathan R. Fink,...