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» How Online Learning Approaches Ornstein Uhlenbeck Processes
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EMNLP
2011
12 years 7 months ago
Training dependency parsers by jointly optimizing multiple objectives
We present an online learning algorithm for training parsers which allows for the inclusion of multiple objective functions. The primary example is the extension of a standard sup...
Keith Hall, Ryan T. McDonald, Jason Katz-Brown, Mi...
KR
1992
Springer
13 years 11 months ago
Learning Useful Horn Approximations
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
Russell Greiner, Dale Schuurmans
AAAI
2006
13 years 8 months ago
Action Selection in Bayesian Reinforcement Learning
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Tao Wang
IROS
2006
IEEE
107views Robotics» more  IROS 2006»
14 years 1 months ago
Learning Sensory-Motor Maps for Redundant Robots
— Humanoid robots are routinely engaged in tasks requiring the coordination between multiple degrees of freedom and sensory inputs, often achieved through the use of sensorymotor...
Manuel Lopes, José Santos-Victor
BMCBI
2008
149views more  BMCBI 2008»
13 years 7 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...