1806 search results - page 178 / 362 » Randomness and halting probabilities |
111
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ADMA
2006
Springer
15 years 7 months ago
2006
Springer
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
146
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UAI
2004
15 years 5 months ago
2004
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
106
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AAAI
1996
15 years 5 months ago
1996
We describe a computer program to assist a clinician with assessing the e cacy of treatments in experimental studies for which treatment assignment is random but subject complianc...
118
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SODA
1996
ACM
15 years 4 months ago
1996
ACM
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For example, unlabelled undirected graphs are generated in O(lg3 n) time using O n2 lg3...
132
Voted
AAAI
1992
15 years 4 months ago
1992
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...