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» Strongly Typed Inductive Concept Learning
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AAAI
2006
13 years 7 months ago
Active Learning with Near Misses
Assume that we are trying to build a visual recognizer for a particular class of objects--chairs, for example--using existing induction methods. Assume the assistance of a human t...
Nela Gurevich, Shaul Markovitch, Ehud Rivlin
ICADL
2003
Springer
159views Education» more  ICADL 2003»
13 years 11 months ago
Ontology Learning for Medical Digital Libraries
Ontologies play an important role in the Semantic Web as well as in digital library and knowledge portal applications. This project seeks to develop an automatic method to enrich e...
Chew-Hung Lee, Jin-Cheon Na, Christopher S. G. Kho...
ICML
1989
IEEE
13 years 10 months ago
Uncertainty Based Selection of Learning Experiences
The training experiences needed by a learning system may be selected by either an external agent or the system itself. We show that knowledge of the current state of the learner&#...
Paul D. Scott, Shaul Markovitch
AAAI
1997
13 years 7 months ago
Representing Sequences in Description Logics
This paper describes an approach for representing and manipulating sequences in description logics (DLs). The key idea is to represent sequences using sux trees, then represent t...
Haym Hirsh, Daniel Kudenko
PAMI
1998
87views more  PAMI 1998»
13 years 5 months ago
Learning Local Languages and Their Application to DNA Sequence Analysis
—This paper concerns an efficient algorithm for learning in the limit a special type of regular languages called strictly locally testable languages from positive data, and its a...
Takashi Yokomori, Satoshi Kobayashi