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COLING
2010
15 years 1 months ago
Boosting Relation Extraction with Limited Closed-World Knowledge
This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
WWW
2008
ACM
16 years 7 months ago
Automatically refining the wikipedia infobox ontology
The combined efforts of human volunteers have recently extracted numerous facts from Wikipedia, storing them as machine-harvestable object-attribute-value triples in Wikipedia inf...
Fei Wu, Daniel S. Weld
CVPR
2011
IEEE
15 years 2 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
SAC
2005
ACM
16 years 13 days ago
Reinforcement learning agents with primary knowledge designed by analytic hierarchy process
This paper presents a novel model of reinforcement learning agents. A feature of our learning agent model is to integrate analytic hierarchy process (AHP) into a standard reinforc...
Kengo Katayama, Takahiro Koshiishi, Hiroyuki Narih...
ALT
2004
Springer
16 years 3 months ago
Probabilistic Inductive Logic Programming
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
Luc De Raedt, Kristian Kersting