Content Gazette - May 2019 - 26
MLSP 2019
IEEE International Workshop on
MACHINE LEARNING FOR SIGNAL PROCESSING
October 13-16, 2019
University of Pittsburgh, Pittsburgh, PA, USA https://www.ieemlsp.cc
Organizing Committee
General
Chair
Murat Akcakaya
University of Pittsburgh, USA
Program
Chairs
Sarah Ostadabbas
Northeastern University, USA
Osman Yagan
Carnegie Mellon University,
USA
Yuejie Chi,
Carnegie Mellon University,
USA
Zhi-Hong Mao
University of Pittsburgh, USA
Finance
Chair
Publicity
and
SoMe Chairs
Advisory
Committee
Marc Van Hulle
KU Leuven, Belgium
Ervin Sejdic
University of Pittsburgh, USA
Raviv Raich
Oregon State University, USA
Deniz Erdogmus
Northeastern University, USA
Zheng-Hua Tan
Aalborg University, Denmark
Schedule
Paper submission
deadline
Decision notification
Camera-ready paper
deadline and advance
registration
June 5
July 30
August 23
Sponsored by
CALL FOR PAPERS
The 29th MLSP workshop, an annual event 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:
Learning theory and modeling
Neural networks and deep learning
Bayesian Learning and modeling
Sequential learning, sequential
decision methods
* Information-theoretic learning
* Graphical and kernel models
* Bounds on performance
* Source separation and independent
component analysis
* Signal detection, pattern
recognition and classification
* Tensor and structured matrix
methods
* Machine learning for big data
* Large scale learning
* Dictionary learning, subspace and
manifold learning
* Resource efficient machine learning
*
*
*
*
* Cognitive information processing
* Bioinformatics applications
* Biomedical applications and neural
engineering
* Speech and audio processing
applications
* Image and video processing
applications
* Intelligent multimedia and web
processing
* Communications applications
* Semi-supervised and unsupervised
learning
* Active and reinforcement learning
* Learning from multimodal data
* Other applications including social
networks, games, smart grid,
security and privacy
MLSP 2019 Data Competition is being organized in conjunction with the workshop. The goal of the competition is to
advance the current state-of-the-art theoretical and practical aspects of machine learning and signal processing domains
Prospective authors are invited to submit a paper using the electronic submission procedure at https://www.ieeemlsp.cc
The presented papers will be published in and indexed by IEEE Xplore.
www.signalprocessingsociety.org
[26]
MAY 2019
https://www.ieemlsp.cc
https://www.ieeemlsp.cc
http://www.signalprocessingsociety.org
Content Gazette - May 2019
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