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SODA
2008
ACM
86views Algorithms» more  SODA 2008»
13 years 11 months ago
Parallel monotonicity reconstruction
We investigate the problem of monotonicity reconstruction, as defined in [3], in a parallel setting. We have oracle access to a nonnegative real-valued function f defined on domai...
Michael E. Saks, C. Seshadhri
UAI
1998
13 years 11 months ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul
UAI
1994
13 years 11 months ago
Approximation Algorithms for the Loop Cutset Problem
We show how to nd a minimum weight loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the rst step in the method of conditioning for inference....
Ann Becker, Dan Geiger
AAAI
2010
13 years 10 months ago
Algorithms for Finding Approximate Formations in Games
Many computational problems in game theory, such as finding Nash equilibria, are algorithmically hard to solve. This limitation forces analysts to limit attention to restricted su...
Patrick R. Jordan, Michael P. Wellman
CORR
2011
Springer
153views Education» more  CORR 2011»
13 years 4 months ago
Partially Linear Bayesian Estimation with Application to Sparse Approximations
—We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum ...
Tomer Michaeli, Daniel Sigalov, Yonina C. Eldar