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FSS
2011
93views more  FSS 2011»
7 years 10 months ago
Upper and lower probabilities induced by a fuzzy random variable
We review two existing interpretations of fuzzy random variables. In the first one, the fuzzy random variable is viewed as a linguistic random variable. In the second case, it re...
Inés Couso, Luciano Sánchez
EOR
2011
111views more  EOR 2011»
7 years 10 months ago
On the distribution of the number stranded in bulk-arrival, bulk-service queues of the M/G/1 form
Bulk-arrival queues with single servers that provide bulk service are widespread in the real world, e.g., elevators in buildings, people-movers in amusement parks, air-cargo deliv...
Aykut F. Kahraman, Abhijit Gosavi
CPC
2011
199views Education» more  CPC 2011»
7 years 10 months ago
Sub-Gaussian Tails for the Number of Triangles in G( n, p)
Let X be the random variable that counts the number of triangles in the binomial random graph G(n, p). We show that for some positive constant c, the probability that X deviates f...
Guy Wolfovitz
CVPR
2011
IEEE
7 years 11 months ago
Variable Grouping for Energy Minimization
This paper addresses the problem of efficiently solving large-scale energy minimization problems encountered in computer vision. We propose an energy-aware method for merging ran...
Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Cha...
ISCI
2010
118views more  ISCI 2010»
8 years 1 months ago
Approximations of upper and lower probabilities by measurable selections
A random set can be regarded as the result of the imprecise observation of a random variable. Following this interpretation, we study to which extent the upper and lower probabili...
Enrique Miranda, Inés Couso, Pedro Gil
RSA
2008
84views more  RSA 2008»
8 years 2 months ago
Random partitions with restricted part sizes
: ForasubsetS ofpositiveintegerslet (n, S)bethesetofpartitionsofnintosummands that are elements of S. For every (n, S), let Mn() be the number of parts, with multiplicity, that ...
William M. Y. Goh, Pawel Hitczenko
DAM
2008
102views more  DAM 2008»
8 years 2 months ago
Formulas for approximating pseudo-Boolean random variables
We consider {0, 1}n as a sample space with a probability measure on it, thus making pseudo-Boolean functions into random variables. We then derive explicit formulas for approximat...
Guoli Ding, Robert F. Lax, Jianhua Chen, Peter P. ...
CORR
2010
Springer
129views Education» more  CORR 2010»
8 years 2 months ago
Estimation in Gaussian Noise: Properties of the Minimum Mean-Square Error
Consider the minimum mean-square error (MMSE) of estimating an arbitrary random variable from its observation contaminated by Gaussian noise. The MMSE can be regarded as a function...
Dongning Guo, Yihong Wu, Shlomo Shamai, Sergio Ver...
JILP
2000
103views more  JILP 2000»
8 years 3 months ago
Comparing and Combining Profiles
How much do two profiles of the same program differ? When has a profile changed enough to warrant reexamination of the profiled program? And how should two or more profiles be com...
Serap A. Savari, Cliff Young
MP
2006
107views more  MP 2006»
8 years 3 months ago
Optimality conditions in portfolio analysis with general deviation measures
Optimality conditions are derived for problems of minimizing a general measure of deviation of a random variable, with special attention to situations where the random variable cou...
R. Tyrrell Rockafellar, Stan Uryasev, Michael Zaba...
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