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» The Structure of First-Order Causality
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ICMLA
2007
13 years 9 months ago
Learning bayesian networks consistent with the optimal branching
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
Alexandra M. Carvalho, Arlindo L. Oliveira
UAI
2008
13 years 9 months ago
Feature Selection via Block-Regularized Regression
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
Seyoung Kim, Eric P. Xing
IJCAI
2003
13 years 9 months ago
Dynamic Bayesian modeling of the cerebral activity
Conventional methods used for the interpretation of activation data provided by functional neuroimaging techniques provide useful insights on what the networks of cerebral structu...
Vincent Labatut, Josette Pastor, Serge Ruff
IS
2011
13 years 2 months ago
Similarity of business process models: Metrics and evaluation
—It is common for large and complex organizations to maintain repositories of business process models in order to document and to continuously improve their operations. Given suc...
Remco M. Dijkman, Marlon Dumas, Boudewijn F. van D...
KDD
1994
ACM
117views Data Mining» more  KDD 1994»
13 years 11 months ago
Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges
We applied TETRAD II, a causal discovery program developed in Carnegie Mellon University's Department of Philosophy, to a database containing information on 204 U.S. colleges...
Marek J. Druzdze, Clark Glymour