posted by user: jiuyong || 4435 views || tracked by 15 users: [display]

TIST-CDI 2014 : ACM Transactions on Intelligent Systems andTechnology (ACM TIST) Special Issue on Causal Discovery and Inference

FacebookTwitterLinkedInGoogle

Link: http://tist.acm.org/CFPs/TIST-SI-CDI.html
 
When N/A
Where N/A
Submission Deadline Mar 28, 2014
Notification Due May 15, 2014
Final Version Due Jun 21, 2014
Categories    artificial intelligence   machine learning   data mining
 

Call For Papers

Due to many requests, the submission deadline has been extended to *28 March, 2014*.

*Call for Papers*
ACM Transactions on Intelligent Systems andTechnology (ACM TIST) Special Issue on Causal Discovery and Inference

Causality plays an important role in explanation, prediction, decision making, and control in many fields of the empirical sciences. Traditionally, causal relationships are identified based on controlled experiments. However, conducting such experiments is usually expensive or even impossible in many cases. Therefore there has been an increasing interest in reasoning in a principled way with causal effect relationships with purely observational data or partially accessible experiments, and significant progress in this line has been made in various fields in the past decades, including computer science, statistics, and philosophy.

Reasoning with causal relationships involves both deductive and inductive tasks. The deductive component asks what can be inferred when the researcher is in possession of certain knowledge or assumptions about the underlying causal process (usually in the form of a causal graph, or features thereof). The inductive component asks how aspects of the graph can be discovered from data when the researcher is willing to make only weak assumptions about the generative process (e.g.,faithfulness). Those are complementary and strongly intertwined tasks, representing a wide spectrum of the trade-off between assumptions and inferential power.

Recently, with the rapid accumulation of huge volume of data, the field of causality is seeing exciting opportunities, as well as greater challenges. This special issue aims at reporting progresses in fundamental principles, practical methodologies, efficient implementations, and applications of causal methods for discovery and inference tasks. The special issue especially welcomes contributions that link data mining research with causality, and solutions to causal problem for large scale data sets.


*Topics of Interest*

We invite high quality submissions related to the following topics (not limited to)
---Identifiability of causal relationships from observational data
---Reasoning with causal effect relationships in problems such as mediation analysis, attribution, heterogeneity
---Integrating experimental (interventional) and observational data for causal inference and learning
---Causal structure learning
---Local causal structure discovery
---Causal discovery from high-dimensional data
---False discovery control in causal discovery
---Real-world problems for causal analysis
---Extensions and connections of data mining approaches for causality methods
---Assessment of causal discovery and inference methods.


*Submission*

On-Line Submission (will be available around 1 February 2014 to accept submissions for the special issue):http://mc.manuscriptcentral.com/tist (please select "Special Issue:Causal Discovery and Inference" as the manuscript type). Details of the journal and manuscript preparation are available on the website: http://tist.acm.org/.


*Important Dates*

Submission deadline: 14 March 2014
Notification of first review: 15 May 2014
Submission of revised manuscript: 21 June 2014
Notification of final acceptance: 22 July 2014
Final manuscript due: 23 August 2014


*Guest Editors*

Kun Zhang, Max Planck Institute for Intelligent Systems,Germany
Jiuyong Li, University of South Australia, Australia
Elias Bareinboim, University of California, Los Angeles, USA
Bernhard Schölkopf, Max Planck Institute for Intelligent Systems, Germany
Judea Pearl, University of California, Los Angeles, USA


*Contact*

cdi@tist.acm.org

Related Resources

ACM--RSAE--EI Compendex, Scopus 2021   ACM--2021 The 3rd International Conference on Robotics Systems and Automation Engineering (RSAE 2021)--EI Compendex, Scopus
IJCAI 2021   30th International Joint Conference on Artificial Intelligence
AIED 2021   Artificial Intelligence in Education
ICDM 2021   21th Industrial Conference on Data Mining
ACIRS--Ei, Scopus 2021   2021 6th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS 2021)--Ei Compendex, Scopus
MLDM 2021   17th International Conference on Machine Learning and Data Mining
ISAPEP 2021   5th International Workshop on Intelligent Systems for Agriculture Production and Environment Protection
Signal 2021   8th International Conference on Signal and Image Processing
ICCSSE--IEEE, Ei & Scopus 2021   IEEE--2021 7th International Conference on Control Science and Systems Engineering (ICCSSE 2021)--Ei Compendex & Scopus
AIET--Scopus, EI Compendex 2021   2021 2nd International Conference on Artificial Intelligence in Education Technology (AIET 2021)--Ei Compendex, Scopus