2017 Workshop on Signal Processing and Machine Learning (SiPML)

Страна: Испания

Город: Barcelona

Дедлайн: 15.07.2017

Даты: 08.11.17 — 10.11.17

Область наук: Технические;

Е-мейл Оргкомитета: ricardo.jorge@uacj.mx

Организаторы: Open University of Catalonia

 

The 2017 Workshop on Signal Processing and Machine Learning (SiPML), is organized by Dr. Ricardo Rodriguez, Dr. Jolanta Mizera-Pietraszko from Autonomous University of Ciudad Juarez, and Opole University, respectively. SiPML will be held in Open University of Catalonia, Barcelona, Spain on November 8-10, 2017, in conjunction with the main conference 12th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2017).

The aim of the workshop is to contribute to the cross-fertilization between the research on Machine Learning (ML) methods and their application to Signal Processing (SP) to initiate collaboration between these areas. ML usually plays an important role in the transition from data storage to decision systems based on large databases of signals such as the obtained from sensor networks, internet services, or communication systems. These systems imply developing both computational solutions and novel models. Signals from real-world systems are usually complex such as speech, music, bio-medical, and multimedia, among others.

1. Topics
Topics of interest include (but not limited to):
• Learning theory
• Subspace/maniforld learning
• Cognitive information processing
• Bayesian and distributed learning
• Neural networks
• Smart Grid, games, social networks
• Classification and pattern recognition
• Computational Intelligence
• Nonlinear signal processing
• Data-driven adaptive systems
• Graphical models and kernel methods
• Data-driven models
• Genomic signals and sequences
• Multimodal data fusion
• Multichannel adaptive signal processing
• Multiset data analysis
• Kernel methods and graphical models
• Perceptual signal processing
• Sparsity-aware learning
• Applications (biomedical signals, biometrix, bioinformatics)

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