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    NIPS
    2007
    121views Information Technology» more  NIPS 2007»
    The Noisy-Logical Distribution and its Application to Causal Inference
    13 years 6 months ago
    The Noisy-Logical Distribution and its Application to Causal Inference
    Download  preprints.stat.ucla.edu
    Alan L. Yuille, Hongjing Lu
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    JMLR
    2010
    134views more  JMLR 2010»
    Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
    12 years 11 months ago
    Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
    Download  parallel.vub.ac.be
    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
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    ICML
    2009
    IEEE
    109views Machine Learning» more  ICML 2009»
    Regression by dependence minimization and its application to causal inference in additive noise models
    14 years 5 months ago
    Regression by dependence minimization and its application to causal inference in additive noise models
    Download  www.kyb.mpg.de
    Bernhard Schölkopf, Dominik Janzing, Jonas Pe...
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    AIME
    2005
    Springer
    119views Artificial Intelligence» more  AIME 2005»
    An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset
    13 years 6 months ago
    An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset
    Download  www.public.asu.edu
    In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
    Xin Zhang, Chitta Baral, Seungchan Kim
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    KDD
    2009
    ACM
    364views Data Mining» more  KDD 2009»
    Causality quantification and its applications: structuring and modeling of multivariate time series
    14 years 5 months ago
    Causality quantification and its applications: structuring and modeling of multivariate time series
    Download  www-ai.cs.uni-dortmund.de
    Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
    Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
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