Zobrazeno 1 - 10
of 1 418
pro vyhledávání: '"clique tree"'
Autor:
Squires, Chandler, Magliacane, Sara, Greenewald, Kristjan, Katz, Dmitriy, Kocaoglu, Murat, Shanmugam, Karthikeyan
A growing body of work has begun to study intervention design for efficient structure learning of causal directed acyclic graphs (DAGs). A typical setting is a causally sufficient setting, i.e. a system with no latent confounders, selection bias, or
Externí odkaz:
http://arxiv.org/abs/2011.00641
Autor:
Zhang, Richard Y.1,2 (AUTHOR), Lavaei, Javad1 (AUTHOR) lavaei@berkeley.edu
Publikováno v:
Mathematical Programming. Jul2021, Vol. 188 Issue 1, p351-393. 43p.
Autor:
Zhang, Richard Y., Lavaei, Javad
Publikováno v:
Mathematical Programming 2020
Clique tree conversion solves large-scale semidefinite programs by splitting an $n\times n$ matrix variable into up to $n$ smaller matrix variables, each representing a principal submatrix of up to $\omega\times\omega$. Its fundamental weakness is th
Externí odkaz:
http://arxiv.org/abs/1710.03475
Publikováno v:
Proceedings of the International Conference on Data Mining (DMIN). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp). p 201, 2016
The problem of categorical data analysis in high dimensions is considered. A discussion of the fundamental difficulties of probability modeling is provided, and a solution to the derivation of high dimensional probability distributions based on Bayes
Externí odkaz:
http://arxiv.org/abs/1708.07025
Autor:
Berry, Anne, Simonet, Geneviève
Algorithm MLS (Maximal Label Search) is a graph search algorithm which generalizes algorithms MCS, LexBFS, LexDFS and MNS. On a chordal graph, MLS computes a peo (perfect elimination ordering) of the graph. We show how algorithm MLS can be modified t
Externí odkaz:
http://arxiv.org/abs/1610.09623
Autor:
ZHENGPING QIU1 zpqiu@hunnu.edu.cn, HANYUAN DENG2 hydeng@hunnu.edu.cn, ZIKAI TANG1 zikaitang@163.com
Publikováno v:
Transactions on Combinatorics. Autumn2024, Vol. 13 Issue 3, p235-255. 21p.
Autor:
Berry, Anne1 berry@isima.fr, Simonet, Geneviève2 genevieve.simonet@umontpellier.fr
Publikováno v:
Algorithms. Mar2017, Vol. 10 Issue 1, p20. 23p.
Cutset conditioning and clique-tree propagation are two popular methods for performing exact probabilistic inference in Bayesian belief networks. Cutset conditioning is based on decomposition of a subset of network nodes, whereas clique-tree propagat
Externí odkaz:
http://arxiv.org/abs/1304.1114
Autor:
Zhang, Nevin Lianwen, Yan, Li
This paper explores the role of independence of causal influence (ICI) in Bayesian network inference. ICI allows one to factorize a conditional probability table into smaller pieces. We describe a method for exploiting the factorization in clique tre
Externí odkaz:
http://arxiv.org/abs/1302.1574
Autor:
Grötschel, M.1, Pulleyblank, W. R.2
Publikováno v:
Mathematics of Operations Research. Nov86, Vol. 11 Issue 4, p537-569. 33p.