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AAAI
1997
15 years 6 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
148
Voted
ATAL
2010
Springer
14 years 11 months ago
Approximate dynamic programming with affine ADDs
The Affine ADD (AADD) is an extension of the Algebraic Decision Diagram (ADD) that compactly represents context-specific, additive and multiplicative structure in functions from a...
Scott Sanner, William T. B. Uther, Karina Valdivia...
MP
2011
14 years 11 months ago
Smoothed analysis of condition numbers and complexity implications for linear programming
We perform a smoothed analysis of Renegar’s condition number for linear programming by analyzing the distribution of the distance to ill-posedness of a linear program subject to...
John Dunagan, Daniel A. Spielman, Shang-Hua Teng
138
Voted
AAAI
2008
15 years 7 months ago
Efficient Haplotype Inference with Answer Set Programming
Identifying maternal and paternal inheritance is essential to be able to find the set of genes responsible for a particular disease. Although we have access to genotype data (gene...
Esra Erdem, Ferhan Türe
135
Voted
ATAL
2006
Springer
15 years 8 months ago
Solving POMDPs using quadratically constrained linear programs
Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...