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» On learning with dissimilarity functions
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GECCO
2006
Springer
140views Optimization» more  GECCO 2006»
15 years 9 months ago
A representational ecology for learning classifier systems
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
James A. R. Marshall, Tim Kovacs
ALT
2002
Springer
16 years 3 months ago
Classes with Easily Learnable Subclasses
In this paper we study the question of whether identifiable classes have subclasses which are identifiable under a more restrictive criterion. The chosen framework is inductive ...
Sanjay Jain, Wolfram Menzel, Frank Stephan
175
Voted
AAAI
2007
15 years 8 months ago
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
165
Voted
ALT
2006
Springer
16 years 3 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
ICALT
2007
IEEE
16 years 13 days ago
The application of IMS Learning Design to Develop Compute-based Educational Game
How can game designers realize the balance of “educational function” and “entertainment” in a Computer-based Educational Game (CEG)? The concept of IMS learning design (LD...
Miaomiao Zeng, Yueliang Zhou