Content Gazette - March 2017 - 11

MLSP2017
IEEE International Workshop on

MACHINE LEARNING FOR SIGNAL PROCESSING
SEPTEMBER 25-28, 2017

ROPPONGI, TOKYO, JAPAN

MLSP2017.CONWIZ.DK
Organizing committee
General
Chairs

Tomoko Matsui
The Institute of Statistical
Mathematics, Japan
Jen-Tzung Chien
National Chiao Tung
University, Taiwan

Program
Chairs

Naonori Ueda
NTT Communication Science
Laboratories, Japan
Shinji Watanabe
Mitsubishi Electric Research
Laboratories, Japan

Finance
Chair

Motoi Okamoto
The Institute of Statistical
Mathematics, Japan

Publicity
Chair

Marc van Hulle
KU Leuven, Belgium

Publication
Chair

Jan Larsen
Technical University of
Denmark, Denmark

Program
Advisory
Committee

Shigeru Katagiri
Doshisha University, Japan
Tülay Adali
University of Maryland,
Baltimore County, USA
Vince Calhoun
University of New Mexico,
USA
Raviv Raich
Oregon State University,
USA

Important Dates and Deadlines
Special session proposals

April 3, 2017

Paper submissions

May 28, 2017

Decision notifications

July 5, 2017

Camera-ready papers and
advance author registration

August 7, 2017

Sponsored by

Copyright by Moyan Brenn, CC-BY-2.0

CALL FOR PAPERS

The 27th MLSP workshop in the series of workshops organized by
the IEEE Signal Processing Society MLSP Technical Committee will
present the most recent and exciting advances in machine learning
for signal processing through keynote talks, tutorials, as well as
special and regular single-track sessions. Prospective authors are
invited to submit papers on relevant algorithms and applications
including, but not limited to:
 Bayesian learning and signal

 Sequential learning and decision







 Source separation
 Tensor and structured matrix







processing
Cognitive information processing
Deep learning techniques
Dictionary learning
Graphical and kernel methods
Independent component
analysis
Information-theoretic learning
Learning theory and algorithms
Pattern recognition and
classification
Bounds on performance
Subspace and manifold learning

methods
methods

 Machine learning from big data
 Scalable learning algorithms
 Applications including: speech,

audio & music, image & video,
biomedical signals & images,
communications, bioinformatics,
biometrics, systems biology,
computational intelligence,
genomic signals & sequences,
social networks, games, smart
grid, security & privacy

MLSP 2017 seeks proposals for Special Sessions that will address
research in emerging or interdisciplinary areas of particular
interest, not covered already by traditional MLSP sessions.
The MLSP Best Student Paper Award will be granted to the best
paper for which a student is the principal author and presenter.

Supported by

Prospective authors are invited to submit a double column
paper of up to six pages using the electronic submission procedure
at http://mlsp2017.conwiz.dk. Accepted papers will be published
on a password-protected website that will be available during the
workshop. The presented papers will be published in and indexed
by IEEE Xplore.

www.signalprocessingsociety.org

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MARCH 2017
http://MLSP2017.CONWIZ.DK http://mlsp2017.conwiz.dk http://www.signalprocessingsociety.org
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