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CORR
2012
Springer
171views Education» more  CORR 2012»
12 years 7 months ago
Discovering causal structures in binary exclusive-or skew acyclic models
Discovering causal relations among observed variables in a given data set is a main topic in studies of statistics and artificial intelligence. Recently, some techniques to disco...
Takanori Inazumi, Takashi Washio, Shohei Shimizu, ...
JMLR
2010
134views more  JMLR 2010»
13 years 6 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
SYNTHESE
2008
112views more  SYNTHESE 2008»
13 years 11 months ago
A sufficient condition for pooling data
We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an "...
Frederick Eberhardt
JMLR
2006
125views more  JMLR 2006»
13 years 11 months ago
A Linear Non-Gaussian Acyclic Model for Causal Discovery
In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data. Such methods make various assumptions on the data generating ...
Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärin...
ESANN
2007
14 years 27 days ago
Exploring the causal order of binary variables via exponential hierarchies of Markov kernels
Abstract. We propose a new algorithm for estimating the causal structure that underlies the observed dependence among n (n ≥ 4) binary variables X1, . . . , Xn. Our inference pri...
Xiaohai Sun, Dominik Janzing
ECSQARU
1999
Springer
14 years 3 months ago
A Critique of Inductive Causation
: In this paper we consider the problem of inducing causal relations from statistical data. Although it is well known that a correlation does not justify the claim of a causal rela...
Christian Borgelt, Rudolf Kruse