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SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
14 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
FUZZIEEE
2007
IEEE
15 years 4 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
95
Voted
STOC
2007
ACM
137views Algorithms» more  STOC 2007»
15 years 10 months ago
Testing k-wise and almost k-wise independence
In this work, we consider the problems of testing whether a distribution over {0, 1}n is k-wise (resp. ( , k)-wise) independent using samples drawn from that distribution. For the...
Noga Alon, Alexandr Andoni, Tali Kaufman, Kevin Ma...
UAI
2001
14 years 11 months ago
A Bayesian Multiresolution Independence Test for Continuous Variables
In this paper we present a method of computing the posterior probability of conditional independence of two or more continuous variables from data, examined at several resolutions...
Dimitris Margaritis, Sebastian Thrun
ICALP
2010
Springer
15 years 2 months ago
Testing Non-uniform k-Wise Independent Distributions over Product Spaces
A discrete distribution D over Σ1 × · · · × Σn is called (non-uniform) k-wise independent if for any set of k indexes {i1, . . . , ik} and for any z1 ∈ Σi1 , . . . , zk ...
Ronitt Rubinfeld, Ning Xie