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AAAI
1997
13 years 9 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
FLAIRS
2009
13 years 5 months ago
Dynamic Programming Approximations for Partially Observable Stochastic Games
Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes wit...
Akshat Kumar, Shlomo Zilberstein
WCNC
2008
IEEE
14 years 2 months ago
A Stochastic Model for Misbehaving Relays in Cooperative Diversity
—Existing cooperative diversity protocols are designed with the inherent assumption that users exhibit cooperative behavior all the time. However, in a practical cooperative wire...
Sintayehu Dehnie, Nasir D. Memon
MP
2006
107views more  MP 2006»
13 years 7 months ago
Convergence theory for nonconvex stochastic programming with an application to mixed logit
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Fabian Bastin, Cinzia Cirillo, Philippe L. Toint
BIRTHDAY
2008
Springer
13 years 9 months ago
The Church-Turing Thesis over Arbitrary Domains
The Church-Turing Thesis has been the subject of many variations and interpretations over the years. Specifically, there are versions that refer only to functions over the natural ...
Udi Boker, Nachum Dershowitz