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IJCAI
2007
13 years 10 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
AAAI
1990
13 years 10 months ago
Backward Model Tracing: An Explanation-Based Approach for Reconstructing Student Reasoning
An original methodology, called backward model tracing to model student performance which features a profitable integration of the bug collection and bug construction techniques i...
Danilo Fum, Paolo Giangrandi, Carlo Tasso
IJCAI
1989
13 years 10 months ago
Using and Refining Simplifications: Explanation-Based Learning of Plans in Intractable Domains
This paper describes an explanation-based approach lo learning plans despite a computationally intractable domain theory. In this approach, the system learns an initial plan using...
Steve A. Chien
CVPR
2005
IEEE
14 years 11 months ago
Feature Kernel Functions: Improving SVMs Using High-Level Knowledge
Kernel functions are often cited as a mechanism to encode prior knowledge of a learning task. But it can be difficult to capture prior knowledge effectively. For example, we know ...
Qiang Sun, Gerald DeJong
AAAI
2010
13 years 11 months ago
An Integrated Systems Approach to Explanation-Based Conceptual Change
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model o...
Scott Friedman, Kenneth D. Forbus