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UAI
1998
13 years 6 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
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
14 years 5 months ago
Approximate Confidence Computation in Probabilistic Databases
Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...
Dan Olteanu, Jiewen Huang, Christoph Koch
BROADNETS
2005
IEEE
13 years 11 months ago
Optimal path selection for ethernet over SONET under inaccurate link-state information
— Ethernet over SONET (EoS) is a popular approach for interconnecting geographically distant Ethernet segments using a SONET transport infrastructure. It typically uses virtual c...
Satyajeet Ahuja, Marwan Krunz, Turgay Korkmaz
AAAI
1992
13 years 6 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
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...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...
SODA
2010
ACM
176views Algorithms» more  SODA 2010»
14 years 2 months ago
Self-improving Algorithms for Convex Hulls
We describe an algorithm for computing planar convex hulls in the self-improving model: given a sequence I1, I2, . . . of planar n-point sets, the upper convex hull conv(I) of eac...
Kenneth L. Clarkson, Wolfgang Mulzer, C. Seshadhri