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68
Voted
ENDM
2002
109views more  ENDM 2002»
14 years 10 months ago
Graph Operations and Zipfian Degree Distributions
The probability distribution on a set S = { 1, 2, . . . , n } defined by Pr(k) = 1/(Hnk), where Hn in the nth harmonic number, is commonly called a Zipfian distribution. In this no...
Walter W. Kirchherr
CORR
2000
Springer
91views Education» more  CORR 2000»
14 years 10 months ago
Algorithmic Theories of Everything
The probability distribution P from which the history of our universe is sampled represents a theory of everything or TOE. We assume P is formally describable. Since most (uncount...
Jürgen Schmidhuber
COMBINATORICS
2004
69views more  COMBINATORICS 2004»
14 years 10 months ago
Convergence in Distribution for Subset Counts Between Random Sets
Erdos posed the problem of how many random subsets need to be chosen from a set of n elements, each element appearing in each subset with probability p = 1/2, in order that at lea...
Dudley Stark
72
Voted
IJAR
2007
55views more  IJAR 2007»
14 years 10 months ago
Theoretical analysis and practical insights on importance sampling in Bayesian networks
The AIS-BN algorithm [2] is a successful importance sampling-based algorithm for Bayesian networks that relies on two heuristic methods to obtain an initial importance function: -...
Changhe Yuan, Marek J. Druzdzel
FUIN
2007
85views more  FUIN 2007»
14 years 10 months ago
Entropies and Co-Entropies of Coverings with Application to Incomplete Information Systems
Different generalizations to the case of coverings of the standard approach to entropy applied to partitions of a finite universe X are explored. In the first approach any cover...
Daniela Bianucci, Gianpiero Cattaneo, Davide Ciucc...
92
Voted
CORR
2007
Springer
128views Education» more  CORR 2007»
14 years 11 months ago
Equivalence of LP Relaxation and Max-Product for Weighted Matching in General Graphs
— Max-product belief propagation is a local, iterative algorithm to find the mode/MAP estimate of a probability distribution. While it has been successfully employed in a wide v...
Sujay Sanghavi
IJAR
2006
103views more  IJAR 2006»
14 years 11 months ago
Computing mean and variance under Dempster-Shafer uncertainty: Towards faster algorithms
In many real-life situations, we only have partial information about the actual probability distribution. For example, under Dempster-Shafer uncertainty, we only know the masses m...
Vladik Kreinovich, Gang Xiang, Scott Ferson
IJAR
2006
125views more  IJAR 2006»
14 years 11 months ago
Computing best-possible bounds for the distribution of a sum of several variables is NP-hard
In many real-life situations, we know the probability distribution of two random variables x1 and x2, but we have no information about the correlation between x1 and x2; what are ...
Vladik Kreinovich, Scott Ferson
IPL
2008
79views more  IPL 2008»
14 years 11 months ago
The probability of "undefined" (non-converging) output in generating the universal probability distribution
In order to generate a universal probability distribution to extrapolate a binary string x of length i, we feed random bits into a universal device, M. When we find an input strin...
Ray J. Solomonoff
COMBINATORICS
2006
162views more  COMBINATORICS 2006»
14 years 11 months ago
Bounding the Partition Function of Spin-Systems
With a graph G = (V, E) we associate a collection of non-negative real weights vV {i,v : 1 i m} uvE{ij,uv : 1 i j m}. We consider the probability distribution on {f : V {1,...
David J. Galvin