Call For Papers
Neurocomputing Special Issue on Dimensionality Reduction for Visual Big Data

Website: http://www.journals.elsevier.com/neurocomputing/call-for-papers/dimensionality-reduction-for-visual-big-data
Submission: http://ees.elsevier.com/neucom/. Please select “SI: Visual Big Data” as the Article Type

Important Dates
Paper Submission: Jul. 1, 2014 First Round Notification: Aug. 1, 2014 Revision: Sep. 1, 2014 Final Decision: Oct. 1, 2014 Publication Date: Dec. 1, 2014Topics of Interest
This special issue is devoted to the publications of high quality papers on technical developments and practical applications around advanced dimensionality reduction techniques for visual big data. It will serve as a forum for recent advances in the fields of multimedia analysis, computer vision, machine learning, etc. We invite original and high quality submissions addressing all aspects of these fields. Relevant topics include, but are not limited to, the following:
Supervised /unsupervised /semi-supervised dimensionality reduction for visual big data Subspace learning for visual big data Manifold learning for visual big data Tensor analysis for visual big data Deep learning for visual big data Non-negative matrix factorization for visual big data Kernel-based dimensionality reduction for visual big data Sparse Representation for visual big data Transfer learning for visual big data Incremental learning for visual big data Efficient learning algorithms for visual big data Binary coding and hashing for visual big data Applications of dimensionality reduction for visual big data.
Guest Editors
Yanwei Pang
Professor
School of Electronic Information Engineering
Tianjin University, Tianjin 300072, China,
pyw@tju.edu.cn
Ling Shao
Associate Professor
Department of Electronic & Electrical Engineering
University of Sheffield, United Kingdom
ling.shao@sheffield.ac.uk