Sciweavers

JMLR
2010
149views more  JMLR 2010»
12 years 11 months ago
Fast Committee-Based Structure Learning
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
Ernest Mwebaze, John A. Quinn
JMLR
2010
134views more  JMLR 2010»
12 years 11 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
JMLR
2010
102views more  JMLR 2010»
12 years 11 months ago
Discover Local Causal Network around a Target to a Given Depth
For a given target node T and a given depth k 1, we propose an algorithm for discovering a local causal network around the target T to depth k. In our algorithm, we find parents,...
You Zhou, Changzhang Wang, Jianxin Yin, Zhi Geng
JMLR
2010
165views more  JMLR 2010»
12 years 11 months ago
Causal Inference
: This review presents empirical researchers with recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving from traditional stati...
Judea Pearl
JMLR
2010
143views more  JMLR 2010»
12 years 11 months ago
Beware of the DAG!
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
A. Philip Dawid
JMLR
2010
93views more  JMLR 2010»
12 years 11 months ago
Distinguishing between cause and effect
We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic late...
Joris M. Mooij, Dominik Janzing
JMLR
2010
105views more  JMLR 2010»
12 years 11 months ago
When causality matters for prediction
Recent evaluations have indicated that in practice, general methods for prediction which do not account for changes in the conditional distribution of a target variable given feat...
Robert E. Tillman, Peter Spirtes
JMLR
2010
126views more  JMLR 2010»
12 years 11 months ago
Causality: Objectives and Assessment
The NIPS 2008 workshop on causality provided a forum for researchers from different horizons to share their view on causal modeling and address the difficult question of assessing...
Isabelle Guyon, Dominik Janzing, Bernhard Schö...
JMLR
2010
105views more  JMLR 2010»
12 years 11 months ago
Causal Discovery as a Game
This paper presents a game theoretic approach to causal discovery. The problem of causal discovery is framed as a game of the Scientist against Nature, in which Nature attempts to...
Frederick Eberhardt
JMLR
2010
157views more  JMLR 2010»
12 years 11 months ago
Causality Challenge: Benchmarking relevant signal components for effective monitoring and process control
A complex modern manufacturing process is normally under consistent surveillance via the monitoring of signals/variables collected from sensors. However, not all of these signals ...
Michael McCann, Yuhua Li, Liam P. Maguire, Adrian ...