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151views
14 years 2 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
FLAIRS
2007
15 years 6 months ago
Random Subsets Support Learning a Mixture of Heuristics
Problem solvers, both human and machine, have at their disposal many heuristics that may support effective search. The efficacy of these heuristics, however, varies with the probl...
Smiljana Petrovic, Susan L. Epstein
NIPS
2008
15 years 5 months ago
A rational model of preference learning and choice prediction by children
Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what childr...
Christopher G. Lucas, Thomas L. Griffiths, Fei Xu,...
ECSCW
2003
15 years 5 months ago
Supporting Collaboration Ubiquitously: An Augmented Learning Environment for Architecture Students
While CSCW research has mostly been focusing on desktop applications there is a growing interest on ubiquitous and tangible computing. We present ethnographic fieldwork and prototy...
Giulio Iacucci, Ina Wagner
144
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NIPS
1994
15 years 5 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...