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JMLR
2010
134views more  JMLR 2010»
15 years 1 months ago
Using Contextual Representations to Efficiently Learn Context-Free Languages
We present a polynomial update time algorithm for the inductive inference of a large class of context-free languages using the paradigm of positive data and a membership oracle. W...
Alexander Clark, Rémi Eyraud, Amaury Habrar...
AAAI
2011
14 years 6 months ago
Using Semantic Cues to Learn Syntax
We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
Tahira Naseem, Regina Barzilay
CIARP
2007
Springer
16 years 14 days ago
Learning in Computer Vision: Some Thoughts
Abstract. It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems l...
Maria Petrou
ILP
2005
Springer
15 years 11 months ago
Learning Teleoreactive Logic Programs from Problem Solving
In this paper, we focus on the problem of learning reactive skills for use by physical agents. We propose a new representation for such procedures, teleoreactive logic programs, al...
Dongkyu Choi, Pat Langley
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
15 years 10 months ago
Metaphor for learning: an evolutionary algorithm
The organizational algorithm is examined as a computational approach to representing interpersonal learning. The structure of the algorithm is introduced and described in context ...
Jody Lee Louse, Alexander Kain, James Hines