MacSeNet 2016 - SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing
Topics/Call fo Papers
SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing
4-8 April 2016, Ilmenau, Germany
www.macsenet.eu/SpringSchool
The SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing Spring School will be of interest to graduate students, researchers and industry professionals working in this fast moving and exciting area. The five day school is split into two components, during three days, a panel of experts will offer lectures and tutorials covering the theory of sparse representations, compressed sensing and related topics, and applications of these methods in areas such as image processing, audio signal processing, and signal processing on graphs. The remaining two days will be devoted to software carpentry, giving researchers the computing skills they need to get more done in less time and with less pain.
Topics and speakers will include:
- Gerald Schuller (Fraunhofer IDMT): Neural Networks and Sparse Coding from the Signal Processing Perspective
- Francis Bach (INRIA): Large Scale Optimization; Probabilistic Modelling
- Mike Davies (University of Edinburgh): Compressed Sensing Theory and Extensions
- Mario Figueiredo (Instituto de Telecomunicações): Convex Optimization in Inverse Problems and Machine Learning
- Sergios Theodoridis (University of Athens): Learning in Reproducing Kernel Hilbert Spaces
- Ian Marshall (University of Edinburgh): Compressed Sensing in MRI
- Wenwu Wang (University of Surrey): Sparse Representation and Dictionary Learning for Source Separation, Localisation and Tracking
- Sacha Krstlovic (Audio Analytic): Audio Event detection in an Industrial Environment
- Karen Egiazarian (Noiseless Imaging): Image Denoising and Enhancement
- Pierre Vandergheynst (EPFL) Graph Signal Processing
- Jakob Abesser (Fraunhofer IDMT): Instrument Centered Parameter Sstimation and Sound Synthesis
The programme will include a Keynote talk by Prof. Karlheinz Brandenburg (Fraunhofer IDMT).
There will also be an opportunity for participants to present a poster, giving a chance to discuss their own work with their peers and the speakers.
How to apply:
To apply, please submit the following information to macsenet-AT-surrey.ac.uk:
* Full name
* Email address
* Phone Number
* Address
* Affiliation
* Your CV
* A cover letter of up to 2000 characters
* A short letter of recommendation from one referee of your choice
* (optional) Title of the poster you would present
For successful applicants there will be a small registration fee of £300 to cover the cost of their meals and accommodation.
Important Dates
2016-01-18 Applications opens
2016-02-26 Deadline for Applications
2016-03-11 Notification of acceptance
2016-04-04 Spring School Starts
Organizers
The SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing is organized and sponsored by the SpaRTaN (Sparse Representations and Compressed Sensing Training Network, www.spartan-itn.eu) Marie Curie Initial Training Network (ITN) funded by the EU Seventh Framework Programme (FP7-PEOPLE-ITN-2013-607290), and the MacSeNet (Machine Sensing Training Network, www.macsenet.eu) Marie Sklodowska-Curie Action Innovative Training Network (ITN) funded by the EU H2020 Programme (H2020-MSCA-ITN-2014-642685).
4-8 April 2016, Ilmenau, Germany
www.macsenet.eu/SpringSchool
The SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing Spring School will be of interest to graduate students, researchers and industry professionals working in this fast moving and exciting area. The five day school is split into two components, during three days, a panel of experts will offer lectures and tutorials covering the theory of sparse representations, compressed sensing and related topics, and applications of these methods in areas such as image processing, audio signal processing, and signal processing on graphs. The remaining two days will be devoted to software carpentry, giving researchers the computing skills they need to get more done in less time and with less pain.
Topics and speakers will include:
- Gerald Schuller (Fraunhofer IDMT): Neural Networks and Sparse Coding from the Signal Processing Perspective
- Francis Bach (INRIA): Large Scale Optimization; Probabilistic Modelling
- Mike Davies (University of Edinburgh): Compressed Sensing Theory and Extensions
- Mario Figueiredo (Instituto de Telecomunicações): Convex Optimization in Inverse Problems and Machine Learning
- Sergios Theodoridis (University of Athens): Learning in Reproducing Kernel Hilbert Spaces
- Ian Marshall (University of Edinburgh): Compressed Sensing in MRI
- Wenwu Wang (University of Surrey): Sparse Representation and Dictionary Learning for Source Separation, Localisation and Tracking
- Sacha Krstlovic (Audio Analytic): Audio Event detection in an Industrial Environment
- Karen Egiazarian (Noiseless Imaging): Image Denoising and Enhancement
- Pierre Vandergheynst (EPFL) Graph Signal Processing
- Jakob Abesser (Fraunhofer IDMT): Instrument Centered Parameter Sstimation and Sound Synthesis
The programme will include a Keynote talk by Prof. Karlheinz Brandenburg (Fraunhofer IDMT).
There will also be an opportunity for participants to present a poster, giving a chance to discuss their own work with their peers and the speakers.
How to apply:
To apply, please submit the following information to macsenet-AT-surrey.ac.uk:
* Full name
* Email address
* Phone Number
* Address
* Affiliation
* Your CV
* A cover letter of up to 2000 characters
* A short letter of recommendation from one referee of your choice
* (optional) Title of the poster you would present
For successful applicants there will be a small registration fee of £300 to cover the cost of their meals and accommodation.
Important Dates
2016-01-18 Applications opens
2016-02-26 Deadline for Applications
2016-03-11 Notification of acceptance
2016-04-04 Spring School Starts
Organizers
The SpaRTaN-MacSeNet Spring School on Sparse Representations and Compressed Sensing is organized and sponsored by the SpaRTaN (Sparse Representations and Compressed Sensing Training Network, www.spartan-itn.eu) Marie Curie Initial Training Network (ITN) funded by the EU Seventh Framework Programme (FP7-PEOPLE-ITN-2013-607290), and the MacSeNet (Machine Sensing Training Network, www.macsenet.eu) Marie Sklodowska-Curie Action Innovative Training Network (ITN) funded by the EU H2020 Programme (H2020-MSCA-ITN-2014-642685).
Other CFPs
Last modified: 2016-01-28 23:31:55