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104
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ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
15 years 8 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
UIST
1994
ACM
15 years 6 months ago
Evolutionary Learning of Graph Layout Constraints from Examples
We propose a new evolutionary method of extracting user preferences from examples shown to an automatic graph layout system. Using stochastic methods such as simulated annealing a...
Toshiyuki Masui
105
Voted
AAAI
1998
15 years 3 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
128
Voted
GPEM
2002
104views more  GPEM 2002»
15 years 2 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
214
Voted
TSE
2010
140views more  TSE 2010»
15 years 26 days ago
Learning a Metric for Code Readability
—In this paper, we explore the concept of code readability and investigate its relation to software quality. With data collected from 120 human annotators, we derive associations...
Raymond P. L. Buse, Westley Weimer