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ATAL
2008
Springer
13 years 11 months ago
Graph Laplacian based transfer learning in reinforcement learning
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
Yi-Ting Tsao, Ke-Ting Xiao, Von-Wun Soo
CVPR
2008
IEEE
14 years 11 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona
SIGGRAPH
2010
ACM
14 years 2 months ago
Learning behavior styles with inverse reinforcement learning
We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
Seong Jae Lee, Zoran Popovic
CGF
2007
151views more  CGF 2007»
13 years 9 months ago
Teaching, Exploring, Learning - Developing Tutorials for In-Class Teaching and Self-Learning
This paper presents an experience report on a novel approach for a course on intermediate and advanced computer graphics topics. The approach uses Teachlet Tutorials, a combinatio...
Steffi Beckhaus, Kristopher J. Blom
ICRA
2009
IEEE
145views Robotics» more  ICRA 2009»
14 years 4 months ago
Learning 3-D object orientation from images
— We propose a learning algorithm for estimating the 3-D orientation of objects. Orientation learning is a difficult problem because the space of orientations is non-Euclidean, ...
Ashutosh Saxena, Justin Driemeyer, Andrew Y. Ng