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DAGSTUHL
2007
15 years 8 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
LREC
2008
150views Education» more  LREC 2008»
15 years 8 months ago
Automatic Translation of Biomedical Terms by Supervised Machine Learning
In this paper, we present a simple yet efficient automatic system to translate biomedical terms. It mainly relies on a machine learning approach able to infer rewriting rules from...
Vincent Claveau
NIPS
2008
15 years 8 months ago
A rational model of preference learning and choice prediction by children
Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what childr...
Christopher G. Lucas, Thomas L. Griffiths, Fei Xu,...
NIPS
2000
15 years 8 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
PRL
2006
129views more  PRL 2006»
15 years 6 months ago
Learning spatial relations in object recognition
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...
Thang V. Pham, Arnold W. M. Smeulders