Connectionists: CFP: Information Fusion Journal - Special Issue on Applications of Ensemble Methods

[Nikunj Oza]

APOLOGIES FOR MULTIPLE COPIES


                        Call for papers for a special issue of

                                    Information Fusion

An International Journal on Multi-Sensor, Multi-Source Information Fusion

                                 An Elsevier Publication
               
                                                On
               
                APPLICATIONS OF ENSEMBLE METHODS

Editor-in-Chief: Dr. Belur V. Dasarathy, FIEEE
d.belur at elsevier.com         http://belur.no-ip.com

Guest Editors: Nikunj C. Oza, Kagan Tumer

The Information Fusion Journal is planning a special issue devoted to 
Applications of Ensemble Methods in Machine Learning and Pattern 
Recognition. Ensembles, also known as Multiple Classifier Systems (MCSs) 
and Committee Classifiers, were originally motivated by the desire to 
avoid relying on just one learned model when only a small amount of 
training data is available. Because of this, most studies on ensembles 
have evaluated their new algorithms on relatively small datasets; most 
notably, datasets from the University of California, Irvine (UCI) 
Machine Learning Repository. However, modern data mining problems raise 
a variety of issues very different from the ones ensembles have 
traditionally addressed. These new problems include too much data; data 
that are distributed, are noisy, and represent changing environments; 
and performance measures different from the standard accuracy 
measurements; among others. The aim of this issue is to examine the 
different applications that raise these modern data mining problems, and 
how current and novel ensemble methods aid in solving these problems.

Manuscripts (which should be original and not previously published or 
presented even in a more or less similar form under any other forum) 
covering new applications as well as the theories and algorithms of 
ensemble learning algorithms developed to address these applications are 
invited. Contributions should be described in sufficient detail to be 
reproducible on the basis of the material presented in the paper.

Topics appropriate for this special issue include, but are not limited to:

· Innovative applications of ensemble methods.
· Novel algorithms that address unique requirements (for example, 
different performance
measures or running time constraints) of an application or a class of 
applications.
· Novel theories developed under assumptions unique to an application or 
a class of applications.
· Novel approaches to distributed model fusion.

Manuscripts should be submitted electronically online at 
http://ees.elsevier.com/inffus (The corresponding author will have to 
create a user profile if one has not been established before at Elsevier.)
Please also send without fail an electronic copy to 
oza at email.arc.nasa.gov (PDF format preferred),

                            Guest Editors
            Nikunj C. Oza and Kagan Tumer

            NASA Ames Research Center
            Mail Stop 269-3
            Moffett Field, CA 94035-1000, USA

            Deadline for Submission: November 30, 2005

-- 
--------------------------------------
Nikunj C. Oza, Ph.D.				Tel: (650)604-2978
Research Scientist				Fax: (650)604-4036
NASA Ames Research Center		E-mail: oza at email.arc.nasa.gov
Mail Stop 269-3					Web: http://ic.arc.nasa.gov/people/oza
Moffett Field, CA 94035-1000
USA