IEEE International Workshop on Machine Learning for Signal Processing

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IEEE International Workshop on Machine Learning for Signal Processing

MLSP2019 - IEEE International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING

OCTOBER 13-16, 2019 |  Pittsburgh, PA, USA |  www.ieeemlsp.cc  | Deadline Extended: 19 June 2019

FINAL CALL FOR PAPERS

The 29th 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:

- 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

- Semi-supervised and unsupervised learning

- Active and reinforcement learning

- Learning from multimodal data

- 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

- Other applications including social networks, games, smart grid, security and privacy

DATA ANALYSIS AND SIGNAL PROCESSING COMPETITION

MLSP 2019 Data Analysis and Signal Processing Competition is being organized in conjunction with the workshop. The goal of competition is to advance the current state-of-the-art in theoretical and practical aspects of machine learning and signal processing domains.

PAPER SUBMISSION

Prospective authors are invited to submit a double column paper of up to six pages using the electronic submission procedure at https://www.ieeemlsp.cc. The presented papers will be published in and indexed by IEEE Xplore.

IMPORTANT DATES AND DEADLINES:

Paper submission deadline extended - June 19, 2019

Decision notification - July 30, 2019

Camera-ready papers and Author advance registration -  August 23, 2019

KEYNOTE SPEAKERS:

Jose C. Principe, Distinguished Professor, Director of Computational NeuroEngineering Laboratory, University of Florida

Jeff Schneider, Research Professor, The Robotics Institute, School of Computer Science, Carnegie Mellon University

Nikolaos Sidiropoulos, Professor and Chair, Electrical and Computer Engineering Department, University of Virginia

TUTORIALS:

Siheng Chen, Research Scientist at Mitsubishi Electric Research Laboratory (MERL). Tutorial Title: Data science with graphs: From social network analysis to autonomous driving

Amir Tahmasebi, Director of Machine Learning and AI, CODAMETRIX, Boston, MA. Tutorial Title: Natural Language Processing for Healthcare Applications

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

Panos Markopoulos, Rochester Institute of Technology, NY, USA

Finance Chair:

Zhi-Hong Mao, University of Pittsburgh, USA

Data Competition Chairs:

Vince Calhoun, University of New Mexico, USA

Rogers Silva, University of New Mexico, USA

Yuhui Du, University of New Mexico, USA

Publicity and Social Media Chairs:

Marc Van Hulle, KU Leuven, Belgium

Ervin Sejdic, University of Pittsburgh, Pittsburgh, PA, USA

Advisory Committee:

Raviv Raich, Oregon State University, USA

Deniz Erdogmus, Northeastern University, Boston, MA, USA

Zheng-Hua Tan, Aalborg University, Aalborg, Denmark

Bhaskar Rao, University of California, San Diego, CA, USA

IEEE Signal Processing Society Liaison

Ulisses Braga-Neto, Texas A&M University,  College Station, TX, USA

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