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» A New Way to Introduce Knowledge into Reinforcement Learning
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CVPR
2010
IEEE
15 years 8 months ago
Beyond Active Noun Tagging: Modeling Contextual Interactions for Multi-Class Active Learning
We present an active learning framework to simultaneously learn appearance and contextual models for scene understanding tasks (multi-class classification). Existing multi-class a...
Behjat Siddiquie, Abhinav Gupta
ICRA
2009
IEEE
125views Robotics» more  ICRA 2009»
15 years 6 months ago
Learning motor primitives for robotics
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...
Jens Kober, Jan Peters
ICIP
1998
IEEE
15 years 3 months ago
Knowledge-based Segmentation of SAR Images
A new approach for the segmentation of still and video SAR images is described in this paper. A priori knowledge about the objects present in the image, e.g., target, shadow, and ...
Steven Haker, Guillermo Sapiro, Allen Tannenbaum
IJCAI
2007
15 years 1 months ago
Change of Representation for Statistical Relational Learning
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
HIS
2003
15 years 1 months ago
Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR
Multiple Classification Ripple Down Rules (MCRDR) is a simple and effective knowledge acquisition technique that produces representations, or knowledge maps, of a human expert’s ...
Richard Dazeley, Byeong Ho Kang