![]() |
| |||||||||||||||
IJAMAS-ELA 2011 : IJAMAS Special Issue on Advances in Ensemble Learning and Its Applications | |||||||||||||||
Link: http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/m-f-abdel-hady/ijamas-el.html | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
Call for Papers
Special Issue on Advances in Ensemble Learning and Its Applications International Journal of Applied Mathematics & Statistics (IJAMAS) One of the most promising areas of data mining and machine learning is ensemble learning, which is used successfully in many real-world applications such as text categorization, optical character recognition, face recognition and computer-aided medical diagnosis. An ensemble consists of a set of individual predictors (such as neural networks or decision trees) whose predictions are combined when classifying a given example. The idea of designing ensembles was originated as an alternative way for improving the performance of individual classifiers by exploiting knowledge derived from different sources. It overcomes the limitation of traditional learning algorithms that construct single classifiers and opens new areas of research. The publications related to different aspects of designing ensemble of classifiers as well as their applications in a variety of domains shows growing interests in the data mining and machine learning community. Accordingly, the aim of this special issue is to bring together researchers to discuss the new theoretical trends and the applications of ensemble learning concepts. Topics of Interest: (include but are not limited to) •Theoretical analysis of ensemble learning •Fusion of multiple-source/multi-sensor data •Bagging and boosting •Methods for classifier selection (Ensemble Pruning) •Combination and Fusion methods •Ensemble learning for classification/regression •Ensemble learning for clustering •Related learning tasks ◦Feature selection with ensembles ◦Multi-label learning with ensembles ◦Multi-instance learning with ensembles ◦Active learning with ensembles ◦Semi-supervised with ensembles •New applications of ensemble learning especially in data mining, medical diagnosis, face recognition, emotion recognition and bioinformatics Paper Submission: The manuscripts should be written in English and submitted in PDF format through the EasyChair submission website (https://www.easychair.org/account/signin.cgi?conf=ijamasel2011) and a copy should be sent to eic.ijamas(at)yahoo.com with a covering letter as given in "Author Instructions" of the journal (http://ceser.res.in/ijamas.html). All manuscripts will be subject to peer review. If finally accepted, the articles must be formatted by the authors according to "Author Instructions" of the journal (http://ceser.res.in/ijamas.html). Important Dates: •Deadline for Paper Submission: 15 January 2011 •Paper Review Notification:15 February 2011 •Final Version Submission: 15 March 2011 •Paper Acceptance Notification: 15 April 2011 •Print Publication: to be announced About IJAMAS Journal: IJAMAS is to publish refereed, well-written original research articles, and studies that describe the latest research and developments in the area of applied mathematics and statistics. This is a broad-based journal covering all branches of mathematics, statistics and interdisciplinary research. It is a peer-reviewed journal and published four times a year by CESER Publications with associations of Centre for Environment, Social & Economic Research, and Indian Society for Development and Environment Research. For more information about the IJSI, please refer to the following URL for details http://ceser.res.in/ijamas.html |
|