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CG
2000
Springer
14 years 1 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
ALT
2006
Springer
14 years 5 months ago
Iterative Learning from Positive Data and Negative Counterexamples
A model for learning in the limit is defined where a (so-called iterative) learner gets all positive examples from the target language, tests every new conjecture with a teacher ...
Sanjay Jain, Efim B. Kinber
ICCV
2011
IEEE
12 years 8 months ago
Incremental On-line Semi-supervised Learning for Segmenting the Left Ventricle of the Heart from Ultrasound Data
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
Gustavo Carneiro, Jacinto C. Nascimento
EWSPT
2003
Springer
14 years 2 months ago
Lessons Learned and Recommendations from Two Large Norwegian SPI Programmes
: Software development is an experimental discipline, i.e. somewhat unpredictable. This suggests that software processes improvement should be based on the continuous iteration of ...
Reidar Conradi, Tore Dybå, Dag I. K. Sj&osla...
AAAI
1998
13 years 10 months ago
Learning to Extract Symbolic Knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...