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AAAI
2000
15 years 6 months ago
Modeling Classification and Inference Learning
Human categorization research is dominated by work in classification learning. The field may be in danger of equating the classification learning paradigm with the more general ph...
Bradley C. Love, Arthur B. Markman, Takashi Yamauc...
APCCM
2009
15 years 6 months ago
Modeling Natural Language Communication in Database Semantics
Database Semantics (DBS) is a computational model of how communicating with natural language works. at a level of abstraction which may be applied to natural and artificial agents...
Roland Hausser
130
Voted
COLING
2010
14 years 12 months ago
Fast, Greedy Model Minimization for Unsupervised Tagging
Model minimization has been shown to work well for the task of unsupervised part-of-speech tagging with a dictionary. In (Ravi and Knight, 2009), the authors invoke an integer pro...
Sujith Ravi, Ashish Vaswani, Kevin Knight, David C...
FGCS
2011
153views more  FGCS 2011»
14 years 12 months ago
Representing distributed systems using the Open Provenance Model
From the World Wide Web to supply chains and scientific simulations, distributed systems are a widely used and important approach to building computational systems. Tracking prov...
Paul T. Groth, Luc Moreau
ECML
2007
Springer
15 years 11 months ago
Learning from Relevant Tasks Only
We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...
Samuel Kaski, Jaakko Peltonen