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Subject: [ E-CFP ] Call for Papers - A Special Issue of IJSI on Manifold Learning
From: <mingji1_(on)_illinois.edu>
Date received: 01 Oct 2012
Deadline: 30 Nov 2012
Start date: -

You are cordially invited to submit your research paper to a
special issue on manifold learning to be published in
International Journal of Software and Informatics (IJSI) (URL:
http://www.ijsi.org). IJSI is a peer-reviewed international
journal with focuses on theoretical foundation and practical
research of software techniques. It has an editorial board
consisting of internationally well-known experts.

1. Theme and topics

In many information analysis tasks, one is often confronted with
thousands to millions-dimensional data, such as images,
documents, videos, web data, bioinformatics data, etc.
Conventional statistical and computational tools are often
severely inadequate for processing and analysing high-dimensional
data due to the curse of dimensionality, where we often need to
conduct inference with a limited number of samples in a very
high-dimensional space. There is a strong intuition that the data
may have a lower dimensional intrinsic representation with low
intrinsic complexity. Recently, various work have considered the
case when the data is sampled from a submanifold embedded in the
much higher dimensional Euclidean space. Learning with full
consideration of the low dimensional manifold structure, or
specifically the intrinsic topological and geometrical properties
of the data manifold is referred to as manifold learning, which
is receiving growing attention in the community in recent years.

This special issue is to attract articles that (a) address the
frontier problems in the scientific principles of manifold
learning, and (b) report empirical studies and applications of
manifold learning algorithms, including but not limited to
pattern recognition, computer vision, web mining, image
processing, bioinformatics and so on.

Below is an incomplete list of potential topics to be covered in
the special issue:
1. Dimensionality reduction based on manifold learning
2. Supervised manifold learning (e.g., classification)
3. Unsupervised manifold learning (e.g., clustering)
4. Semi-supervised manifold learning
5. Manifold regularization
6. Manifold ranking
7. Manifold alignment
8. Manifold learning theory
9. Kernel methods based on manifold learning
10. Manifold learning with noisy and incomplete data
11. Efficiency issues in manifold learning
12. Algebraic, geometric, and topological methods for manifold
13. Empirical study of the performance of manifold learning
14. Applications of manifold learning

2. Requirements of submissions

All submissions must meet the following requirements.
(a) The paper must be written in English.
(b) All submissions must be typeset in the journal's format. A
    format template can be downloaded from the journal's website
    at the following URL:
(c) There is no strict restriction on the length of a submission.
    All the submissions will be evaluated based on the quality of
    the work.
(d) The submission must be the authors' own original work and it
    must have not been formally published or submitted for the
    consideration of publication anywhere else.
(e) If a submission is an extension of a workshop or conference
    paper, it must contain a substantial amount of new material.
    As a guideline, it should contain at least 300f new
    material. In that case, the author must state the differences
    of the submission from existing publications in a cover
    letter, and include the workshop/conference paper(s) together
    with the submission for the editor to check if the extension
    and revision is satisfactory.

4. How to submit

All submissions must be in the pdf format and uploaded to the
special issue's online submission system at the following URL:

5. Review of the papers

All the submissions will be peer reviewed by at least two
experienced active researchers in the related subject area. The
review process and quality criteria will follow the journal's
review process protocol and standard. The decisions on acceptance
of each paper will be based on the reviewers' reports on the
quality of the submission.

6. Important dates

November 30, 2012: Deadline for paper submission. March 15, 2013:
Notification of the first round of review results. May 15, 2013:
Deadline for submitting the revised versions. August 1, 2013:
Notification of the final decision of acceptance. September 1,
2013: Deadline for camera-ready submission.

6. Contact details of the guest editor

Prof. Xiaofei He, State Key Lab of CAD&CG, Zhejiang University,
Hangzhou 310058, China. Tel: +86 -571-88206681 Fax: +86
-571-88206680 Email: xiaofeihe_(at)_gmail.com ,

Ming Ji Data Mining Research Group Data and Information Systems
Research Laboratory Department of Computer Science University of
Illinois at Urbana-Champaign mingji1_(at)_illinois.edu


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