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HIS
2003
14 years 11 months ago
A Hybrid Approach for Learning Parameters of Probabilistic Networks from Incomplete Databases
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...
S. Haider
WSC
1997
14 years 11 months ago
Long-Lasting Transient Conditions in Simulations with Heavy-Tailed Workloads
Recent evidence suggests that some characteristics of computer and telecommunications systems may be well described using heavy tailed distributions — distributions whose tail d...
Mark Crovella, Lester Lipsky
AAAI
1996
14 years 11 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt
UAI
1996
14 years 11 months ago
A Qualitative Markov Assumption and Its Implications for Belief Change
The study of belief change has been an active area in philosophy and AI. In recent years, two special cases of belief change, belief revision and belief update, have been studied ...
Nir Friedman, Joseph Y. Halpern
GECCO
2008
Springer
147views Optimization» more  GECCO 2008»
14 years 11 months ago
On selecting the best individual in noisy environments
In evolutionary algorithms, the typical post-processing phase involves selection of the best-of-run individual, which becomes the final outcome of the evolutionary run. Trivial f...
Wojciech Jaskowski, Wojciech Kotlowski