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184
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AIR
2006
107views more  AIR 2006»
15 years 5 months ago
Just enough learning (of association rules): the TAR2 "Treatment" learner
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...
Tim Menzies, Ying Hu
CORR
2012
Springer
183views Education» more  CORR 2012»
14 years 19 days ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
ATAL
2008
Springer
15 years 7 months ago
Automated design of scoring rules by learning from examples
Scoring rules are a broad and concisely-representable class of voting rules which includes, for example, Plurality and Borda. Our main result asserts that the class of scoring rul...
Ariel D. Procaccia, Aviv Zohar, Jeffrey S. Rosensc...
141
Voted
CSREAEEE
2007
136views Business» more  CSREAEEE 2007»
15 years 6 months ago
Virtual Apparatus Framework Approach to Constructing Adaptive Tutorials
- We present the Adaptive eLearning Platform (AeLP) – a platform solution for creating rich, interactive, and highly visual, adaptive eLearning activities designed using Virtual ...
Dror Ben-Naim, Nadine Marcus, Michael Bain
ICIC
2007
Springer
15 years 11 months ago
Usage of Hybrid Neural Network Model MLP-ART for Navigation of Mobile Robot
We suggest to apply the hybrid neural network based on multi layer perceptron (MLP) and adaptive resonance theory (ART-2) for solving of navigation task of mobile robots. This appr...
Andrey Gavrilov, Sungyoung Lee