CfP: SPARS 2017, Lisbon, Portugal, June 5-8, 2017, Submission deadline (EXTENDED): January 3, 2017 **

 

 

Mark just sent me the following:

Dear Igor, 

Readers of Nuit Blanche may like to know that, following several requests, the SPARS 2017 deadline has been extended over the holiday period to  ** Tuesday 3 January 2017 **.  (The new deadline is strict: no further extension will be possible.)
As regular readers of your blog will know, the last few weeks have been a busy time for many people. We would like to propose that finishing off and submitting a one-page abstract for SPARS 2017 (plus one additional page for figures and references), and looking forward to presenting in Lisbon, Portugal in June 2017, will be an ideal way to relax over the holiday period, before the New Year begins in earnest! 

Best wishes, Mark

==============================

 SPARS 2017

  Signal Processing with Adaptive Sparse Structured Representations

  Lisbon, Portugal - June 5-8, 2017

  ** Submission deadline (EXTENDED): January 3, 2017 **

  http://spars2017.lx.it.pt/

  ------------------------------------------

CALL FOR PAPERS

The Signal Processing with Adaptive Sparse Structured Representations
(SPARS) workshop aims to bring together people from statistics,
engineering, mathematics, and computer science, fostering the exchange
and dissemination of new ideas and results, both applied and
theoretical, on the general area of sparsity-related techniques and
computational methods, for high dimensional data analysis, signal
processing, and related applications.

Contributions (talks and demos) are solicited as one-page abstracts,
which may extend to a second page in order to include figures, tables
and references. Talks should present recent and novel research
results. We welcome abstract submissions for technological
demonstrations of the mathematical topics within our scope.

Topics of interest include (but are not limited to):

 * Sparse coding and representations, and dictionary learning
 * Sparse and low-rank approximation algorithms
 * Compressive sensing and learning
 * Dimensionality reduction and feature extraction
 * Sparsity in approximation theory, information theory, and statistics
 * Low-complexity/low-dimensional regularization
 * Statistical/Bayesian models and algorithms for sparsity
 * Sparse network theory and analysis
 * Sparsity and low-rank regularization
 * Applications

PLENARY SPEAKERS:

 * Yoram Bresler, University of Illinois, USA
 * Volkan Cevher, École Polytechnique Fédérale de Lausanne, Switzerland
 * Jalal Fadili, École Nationale Supérieure d'Ingénieurs de Caen, France
 * Anders Hansen, University of Cambridge, UK
 * Gitta Kutyniok, Technische Universität Berlin, Germany
 * Philip Schniter, Ohio State University, USA
 * Eero Simoncelli, Howard Hughes Medical Institute, NYU, USA
 * Rebecca Willett, University of Wisconsin, USA

VENUE:

SPARS 2017 will be held at Instituto Superior Técnico (IST), the
engineering school of the University of Lisbon, Portugal.

IMPORTANT DATES:

** Submission deadline (EXTENDED): January 3, 2017 **

* Notification of acceptance: March 27, 2017
* Summer School: May 31-June 2, 2017 (tbc)
* Workshop: June 5-8, 2017

CHAIRS:

 Mario A. T. Figueiredo, Instituto Superior Técnico
 Mark Plumbley, University of Surrey


FURTHER INFORMATION:  http://spars2017.lx.it.pt/

 
 
 
 
 

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CfP: SPARS 2017, Signal Processing with Adaptive Sparse Structured Representations

 

 

 

  Mark just sent me the following:

 

 

Dear Igor, 

A quick reminder for Nuit Blanche readers:
The deadline for submissions to SPARS 2017 is just 2 weeks away, on 12 December!
Best wishes, 

Mark

 

Here is the announcement:

 

================================================

 

  SPARS 2017

  Signal Processing with Adaptive Sparse Structured Representations

  Lisbon, Portugal - June 5-8, 2017

  Submission deadline: December 12, 2016

  http://spars2017.lx.it.pt/

  ------------------------------------------

CALL FOR PAPERS

The Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop aims to bring together people from statistics, engineering, mathematics, and computer science, fostering the exchange and dissemination of new ideas and results, both applied and theoretical, on the general area of sparsity-related techniques and computational methods, for high dimensional data analysis, signal processing, and related applications.

Contributions (talks and demos) are solicited as one-page abstracts, which may extend to a second page in order to include figures, tables and references. Talks should present recent and novel research results. We welcome abstract submissions for technological demonstrations of the mathematical topics within our scope.

Topics of interest include (but are not limited to):

 * Sparse coding and representations, and dictionary learning
 * Sparse and low-rank approximation algorithms
 * Compressive sensing and learning
 * Dimensionality reduction and feature extraction
 * Sparsity in approximation theory, information theory, and statistics
 * Low-complexity/low-dimensional regularization
 * Statistical/Bayesian models and algorithms for sparsity
 * Sparse network theory and analysis
 * Sparsity and low-rank regularization
 * Applications including but not limited to: communications,
   geophysics, neuroscience, audio & music, imaging, denoising, genetics.

PLENARY SPEAKERS:

 * Yoram Bresler, University of Illinois, USA
 * Volkan Cevher, École Polytechnique Fédérale de Lausanne, Switzerland
 * Jalal Fadili, École Nationale Supérieure d'Ingénieurs de Caen, France
 * Anders Hansen, University of Cambridge, UK
 * Gitta Kutyniok, Technische Universität Berlin, Germany
 * Philip Schniter, Ohio State University, USA
 * Eero Simoncelli, Howard Hughes Medical Institute, NYU, USA
 * Rebecca Willett, University of Wisconsin, USA

VENUE:

SPARS 2017 will be held at Instituto Superior Técnico (IST), the
engineering school of the University of Lisbon, Portugal.

IMPORTANT DATES:

* Submission deadline: December 12, 2016
* Notification of acceptance: March 27, 2017
* Summer School: May 31-June 2, 2017 (tbc)
* Workshop: June 5-8, 2017

CHAIRS:

 Mario A. T. Figueiredo, Instituto Superior Técnico
 Mark Plumbley, University of Surrey


FURTHER INFORMATION:  http://spars2017.lx.it.pt/

============================================================

Prof Mark D Plumbley
Professor of Signal Processing
Centre for Vision, Speech and Signal Processing (CVSSP)
University of Surrey, Guildford, Surrey, GU2 7XH, UK
Email: m.plumbley@surrey.ac.uk

 
 
 
 
 

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Fourth BASP Frontiers Workshop, Villars-sur-Ollon, Switzerland, Jan 29-Feb 03 2017

Yves just sent methe following:

Hi Igor
May I ask you to post this BASP Frontiers workshop announcement ...?
Thanks in advance
Cheers
Yves

Sure Yves !

******************
Dear Colleague

The 4th BASP Frontiers workshop will take place from Jan 29 to Feb 03 2017 in its traditional Ski Resort of the Swiss Alps.

This year’s scientific program is just as cutting-edge as usual, on the theoretical signal processing, biomedical imaging, and astronomical data processing fronts.

The all-inclusive 4-star venue organisation should as always help you relax and focus on interdisciplinary science.

Abstract submission window is Sept 1 - Oct 1 2016, both for researchers willing to submit an abstract for deluxe poster contribution and for invited contributions. All abstracts are subject to peer review.

All info on baspfrontiers.org

Miki Lustig, Jason McEwen, Phil Schniter - Area Chairs

Yves Wiaux - Chair

******************

________________________________
Professor Yves Wiaux
Head of the BASP research group
Institute of Sensors, Signals & Systems
Heriot-Watt University, Edinburgh
basp.eps.hw.ac.uk

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Meeting (in French) Co-conception de systèmes hybrides : quand l'instrumentation et les traitements numériques se rencontrent., June 17th, 2016

Yohann let me know of this French meeting coming up next month at Telecom ParisTech. It is very interesting as imaging systems are more and more going to be judged not on the quality of the images produced but also their ability to provide answers following other metrics (think classification). At that point, these metrics will need to be part of the hardware design process. This echoes a little bit the Great Convergence bit ( see recently my recent non-presentation "The Great Convergence" or How ML/DL is Disrupting Sensor Design)  Here is the announcement:

 

 

Co-conception de systèmes hybrides : quand l'instrumentation et les traitements numériques se rencontrent.

Nous vous rappelons que, afin de garantir l'accès de tous les inscrits aux salles de réunion, l'inscription aux réunions est gratuite mais obligatoire.
S'inscrire à la réunion.

Inscriptions

5 personnes membres du GdR ISIS, et 2 personnes non membres du GdR, sont inscrits à cette réunion.
Capacité de la salle : 100 personnes.

Annonce

L'objectif de cette réunion est de discuter des nouvelles approches de conception de nouveaux systèmes d'acquisition pour lesquels le dispositif d'imagerie, de détection ou de mesure est fortement associé aux traitements numériques.
Dans de nombreux domaines, tels que la photographie numérique, la microscopie, l'astronomie ou l'imagerie radar, de nouveaux dispositifs d'acquisition sont développés pour dépasser les performances des systèmes traditionnels, en termes de qualité de signal, d'encombrement, ou pour leur ajouter de nouvelles fonctionnalités. Le principe est d'utiliser un dispositif d'acquisition, autrement dit un instrument, qui favorise l'efficacité des traitements, quitte à dégrader la qualité du signal brut en sortie du détecteur. Ceci donne lieu au développement de nouveaux systèmes "non conventionnels" ou "hybrides", pour lesquels l'instrument et les traitements sont indissociables.
L'enjeu principal de la conception de ces nouveaux systèmes est alors d'optimiser simultanément les paramètres de l'instrument et des traitements. On parle alors de conception conjointe ou co-conception. Cette nouvelle approche repose alors sur :

1. la définition de nouveaux critères de conception caractérisant la performance globale du système en lien avec sa fonctionnalité
2. l'utilisation de ces critères pour optimiser conjointement les paramètres de l'instrument et des traitements.

Lors de cette journée seront abordées plusieurs thématiques :

• les nouvelles technologies (optique, détecteur, etc.) qui favorisent les traitements
• les traitements associés à ces nouvelles solutions
• la modélisation globale de la performance des systèmes, en lien avec leurs fonctionnalités
• l'optimisation conjointe des paramètres d'un système pour une fonctionnalité donnée.

Orateurs invités

Sabine Süsstrunk (EPFL) Neus Sabater (Technicolor) et Wolf Hauser (DxO)

Organisateurs

Pauline Trouvé (Onera), Matthieu Boffety (IOGS), Yohann Tendero (CNRS LTCI, Télécom ParisTech, Univ Paris-Saclay), Andrés Almansa (CNRS LTCI, Télécom ParisTech, Univ Paris-Saclay).

Appel à participation

Si vous souhaitez effectuer un exposé ou présenter un poster lors de cette journée, merci d'envoyer un résumé de votre contribution (1 page) avant le 17 mai 2016 à Pauline Trouvé (pauline.trouve@onera.fr), Andrés Almansa (andres.almansa@telecom-paristech.fr), Matthieu Boffety (matthieu.boffety@institutoptique.fr), ou Yohann Tendero (yohann.tendero@telecom-paristech.fr).

 
 
 
 
 
 
 
 

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@ICLR2016 Periscopes / 4th edition of CoSeRa / ITWIST'16 registration is now open / Workshop on “Networks: learning, information and complexity” at the Institut Henri Poincaré, Paris, May 18-20, 2016.

 First, the @ICLR2016 twitter account features a few Periscopes of the talks going on right now at ICLR in Puerto Rico. We may look into this in our future Paris Machine Learning meetups.

Also, Ludger Prünte let me know of the following announcement:

Dear Igor,

thank you very much for your blog that was one of my major sources about the development of CS during the last years.

Currently, we are organizing the 4th edition of CoSeRa, the "International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing" (http://workshops.fhr.fraunhofer.de/cosera/) that will take place in Aachen (Aix-la-Chapelle) in Germany in September and may be of interest for your audience. After three previous workshops in Bonn and Pisa, we hope to bring together again experts, research engineers, and scientists working in the field of Compressive Sensing and Radar/SAR. In contrast to the original call for papers, we postponed the paper submission deadline to 14 May.

Best regards,
Ludger

 Thanks Ludger ! From the page:

Following the success of the previous editions of the workshop on compressive sensing applied to radar, we are pleased to announce the 4th Int. Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa 2016). It will be held in Aachen (Germany) on 19-22 September 2016. The aim of CoSeRa is to bring experts of Compressive Sensing (CS)and radar/sonar/EO/IR signal processing and remote sensing together to explore the state-of-the-art in development of CS techniques for different areas of applications and to turn out its advantages or possible drawbacks compared to classical solutions.

Topics of interest include (but are not limited to):

• + Foundations and concepts of Compressive Sensing
• + Algorithms for CS signal reconstruction
• + Mathematical aspects of Compressive Sensing in imaging systems
• + Sparsity of radar/sonar/EO/IR signals
• + Applications of sparse sensing in radar/sonar/EO/IR
• + Compressive sensing for SAR Tomography (TomoSAR)
• + Compressive sensing for SAR Interferometry (InSAR)
• + Compressive sensing for Inverse SAR (ISAR)

 

• + Target detection based on compressive sensing
• + Compressive sensing for slow GMTI
• + Co-prime sampling in radar/sonar/EO/IR systems
• + Co-prime array processing in radar/sonar/EO/IR systems
• + Nested sampling in radar/sonar/EO/IR systems
• + Nested array processing in radar/sonar/EO/IR systems
• + Sparse sensing in synthetic aperture imaging systems
• + Design and implementation of circuits/systems based on CS

Radar/SAR awaits Compressed Sensing
Compressed sensing (CS) techniques offer a mathmatical framework for the detection and allocation of sparse signals with a reduced number of samples. Today, modern radar systems operate with high bandwidths - demanding high sample rates according to the Shannon-Nyquist theorem - and a huge number of single elements for phased array antennas.
Often only a small amount of target parameters is the final output, raising the question, whether CS could be a good means to reduce data size, complexity, weight, power consumption and costs of radar systems. The amount of publications addressing the application of CS to radar is still limited, leaving open a number of questions.

 Thomas sent an email out mnetioning that ITWIST'16 registration is now open:

ITWIST'€™16 - REGISTRATION OPEN The third edition of the "€œinternational - Traveling Workshop on Interactions between Sparse models and Technology"€ (iTWIST) is coming to Aalborg, the beautiful main city of Northern Jutland in Denmark. The workshop will be located on the campus of Aalborg University with excellent connections to the city center and less than 20 minutes from Aalborg'€™s international airport. The workshop aims to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For this edition, iTWIST'€™16 will feature 9 invited talks, as well as oral presentations and poster session.
Registration for the workshop is now open. The registration fees (200€) will include all lunches, coffee breaks and the social event (more information on the iTWIST'16 website).

iTWIST'€™16 WEBSITE: http://itwist16.es.aau.dk
Dates: 24th to 26th of August, 2016.

INVITED SPEAKERS

For this edition, the workshop is honored by the participation of the following renowned speakers:

Lieven Vandenberghe (UCLA, USA)	Gerhard Wunder (TU-Berlin, Germany)	Holger Rauhut (RWTH, Germany)
Petros Boufounos (MERL, USA)	Florent Krzakala (ENS, France)	Phil Schniter (Ohio State U., USA)
Karin Schnass (Innsbruck U., Austria)	Rachel Ward (Texas U., Austin, USA)	Bogdan Roman (Cambridge U., UK)

IMPORTANT DATES

Feb. 1, 2016  ......  2-page paper submission opening	Apr. 1, 2016 ..................  Registration opens
Apr. 29, 2016 ...... Paper submission ends	May 13, 2016  ....  Confirmation of accepted papers
May 31, 2016 ..................... Program finalised	Aug. 1, 2016 ..................  Registration closes
June 17, 2016 ............  Final manuscript due	Aug. 24 – 26, 2016  ...........  Workshop (3 days)

LOCAL AND SCIENTIFIC ORGANISING COMMITTEES

SCIENTIFIC ORGANISING COMMITTEE:  Thomas Arildsen (AAU, Denmark)  Morten Nielsen (AAU, Denmark)  Laurent Jacques (UCL, Belgium)  Pascal Frossard (EPFL, Switzerland)  Pierre Vandergheynst (EPFL, Switzerland)  Sandrine Anthoine (I2M, Aix-Marseille U., France)  Yannick Boursier (CPPM, Aix-Marseille U., France)  Aleksandra Pizurica (Ghent U., Belgium)  Christine De Mol (ULB, Belgium)  Christophe De Vleeschouwer (UCL, Belgium). LOCAL ORGANISING COMMITTEE:  Thomas Arildsen (AAU, Denmark)  Morten Nielsen (AAU, Denmark)

On behalf of the organising committee, Thomas Arildsen

 Julie pointed out the following workshop coming up at IHP

Workshop on “Networks: learning, information and complexity” at the Institut Henri Poincaré, Paris, on May 18-20, 2016.

---

Organized by Emmanuel Abbe (Princeton University), Sébastien Bubeck (MSR), Marc Lelarge (Inria) and Laurent Massoulié (MSR-Inria Joint Centre).

The workshop will be devoted to questions of learning, information and complexity in the context of networks. Specific topics of interest include: inference of network structure, community detection, synthesis of efficient random forests and deep neural networks, approaches from statistical physics, and limit objects of graph sequences.
Attendance is open and free, but for planning reasons we require attendees to register

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CfP: ITWIST’16 – international Traveling Workshop on Interactions between Sparse models and Technology” (iTWIST)

Thomas just sent me the following reminder:

 

 This is a gentle reminder that 2-page papers for iTWIST 2016 are due Friday, the 11th of March.
Registration for the workshop will open within a few days.

— ITWIST’16 – CALL FOR PAPERS —

The third edition of the “international - Traveling Workshop on Interactions between Sparse models and Technology” (iTWIST) is coming to Aalborg, the beautiful main city of Northern Jutland in Denmark. The workshop will be located on the campus of Aalborg University with excellent connections the city center and less than 20 minutes from Aalborg’s international airport. The workshop aims to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For this edition, iTWIST’16 will feature 9 invited talks, 10 oral presentations and 40 posters.

iTWIST’16 WEBSITE: http://itwist16.es.aau.dk

– TOPICS OF INTEREST –

iTWIST’16 welcomes 2-page paper submissions on any aspects of the following themes, all related to the theory, application and generalisation of the “sparsity paradigm”:

Sparsity-driven data sensing and processing	Matrix/manifold sensing/processing
Approximate probabilistic inference for sparse problems	Sparse machine learning and inference
Blind inverse problems and dictionary learning	Optimisation for sparse modelling
Information theory, geometry and randomness	Sparsity? What’s next?
Application of sparse models in non-convex/non-linear inverse problems	Complexity/accuracy tradeoffs in numerical methods and optimisation
Electronic/optical compressive sensors (hardware)

– INVITED SPEAKERS –

For this edition, the workshop is honored by the participation of the following renowned speakers:

Lieven Vandenberghe (UCLA, USA)	Gerhard Wunder (TU-Berlin, Germany)	Holger Rauhut (RWTH, Germany)
Petros Boufounos (MERL, USA)	Florent Krzakala (ENS, France)	Phil Schniter (Ohio State U., USA)
Karin Schnass (Innsbruck U., Austria)	Rachel Ward (Texas U., Austin, USA)	Bogdan Roman (Cambridge U., UK)

– IMPORTANT DATES –

Feb. 1, 2016  ......  2-page paper submission opening	Mar. 1, 2016 ..................  Registration opens
Mar. 11, 2016 ...... Paper submission ends	May 13, 2016 ..................... Program finalised
May 13, 2016  ....  Confirmation of accepted papers	Aug. 1, 2016 ..................  Registration closes
June 17, 2016 ............  Final manuscript due	Aug. 24, 2016 ...................  Workshop starts

(Detailed submission guidelines are provided on the iTWIST’16 website)

– LOCAL AND SCIENTIFIC ORGANISING COMMITTEES –

SCIENTIFIC ORGANISING COMMITTEE:  Thomas Arildsen (AAU, Denmark)  Morten Nielsen (AAU, Denmark)  Laurent Jacques (UCL, Belgium)  Pascal Frossard (EPFL, Switzerland)  Pierre Vandergheynst (EPFL, Switzerland)  Sandrine Anthoine (I2M, Aix-Marseille U., France)  Yannick Boursier (CPPM, Aix-Marseille U., France)  Aleksandra Pizurica (Ghent U., Belgium)  Christine De Mol (ULB, Belgium)  Christophe De Vleeschouwer (UCL, Belgium).
LOCAL ORGANISING COMMITTEE:  Thomas Arildsen (AAU, Denmark)  Morten Nielsen (AAU, Denmark)

Please feel free to forward this call for papers to anyone interested and distribute it anywhere you like. You can find a PDF version on the workshop website.
On behalf of the organising committee,
Thomas Arildsen

 
 
 

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iTWIST'16, International Traveling Workshop on Interactions Between Sparse Models and Technology, Aalborg, Denmark 24th-26th of August 2016

 Thomas posted this announcement on the G+ group: (I was surprised the word Hardware did not get to be mentioned for a meeting featuring how CS is crossing over to technology. I am sure this oversight will be addressed (wink-wink people).

International Traveling Workshop on Interactions Between Sparse Models and Technology

The aim of the iTWIST workshop is to foster collaboration between international scientific teams for developing new theories, applications and generalizations of the “sparsity paradigm”. This is why this event emphasizes dissemination of ideas through both specific oral/poster presentations and free discussions.

For this edition, iTWIST’16 will feature invited talks, oral presentations and posters. The workshop welcomes 2-page paper submissions on any aspects of the following themes:

Themes

• Sparsity-driven data sensing and processing (e.g., optics, computer vision, genomics, biomedical, digital communication, channel estimation, astronomy)
• Application of sparse models in non-convex/non-linear inverse problems (e.g., phase retrieval, blind deconvolution, self calibration)
• Approximate probabilistic inference for sparse problems
• Sparse machine learning and inference
• "Blind" inverse problems and dictionary learning
• Optimization for sparse modelling
• Information theory, geometry and randomness
• Sparsity? What's next?
  • Discrete-valued signals
  • Union of low-dimensional spaces,
  • Cosparsity, mixed/group norm, model-based, low-complexity models, ...
• Matrix/manifold sensing/processing (graph, low-rank approximation, ...)
• Complexity/accuracy tradeoffs in numerical methods/optimization

CALL FOR PAPERS

PAPER SUBMISSION AND FORMATTING INSTRUCTIONS WILL BE AVAILABLE IN A FEW DAYS

Plenary Speakers

List of confirmed speakers - we will be updating this list continuously as the invited speakers confirm their participation.

• Lieven Vandenberghe - University of California, Los Angeles - homepage
• Gerhard Wunder - TU Berlin & Fraunhofer Institute - homepage
• Holger Rauhut - RWTH Aachen - homepage
• Petros Boufounos - Mitsubishi Electric Research Labs - homepage
• Florent Krzakala - ENS Paris - homepage
• Phil Schniter - Ohio State University - homepage
• Karin Schnass - University of Innsbruck - homepage
• Rachel Ward - University of Texas at Austin - homepage
• Bogdan Roman - University of Cambridge - homepage

Important Dates

• 1st of February 2016 - 2-page paper submission opening
• 1st of March 2016 - Registration opens (reduced-rate early-bird registration until 1st of July)
• 11th of March 2016 - Paper submission ends
• 13th of May 2016 - Confirmation of accepted papers
• 13th of May 2016 - Program finalized
• 17th of June 2016 - Final manuscript due
• 1st of August 2016 - Registration closes
• 24th of August 2016 - Workshop starts

Organising Committee

• Thomas Arildsen (general chair)
  Department of Electronic Systems at Aalborg University - homepage.
• Morten Nielsen (co-chair)
  Department of Mathematical Sciences at Aalborg University - homepage.
• Laurent Jacques
  Institute of Information and Communication Technologies, Electronics and Applied Mathematics at Université catholique de Louvain - homepage.
• Pascal Frossard
  Electrical Engineering Institute at École Polytechnique Fédérale de Lausanne - homepage.
• Pierre Vandergheynst
  Electrical Engineering Institute at École Polytechnique Fédérale de Lausanne - homepage.
• Sandrine Anthoine
  Marseille Institute of Mathematics, at Aix-Marseille Université and CNRS - homepage.
• Yannick Boursier
  Center for Particle Physics of Marseille, at Aix-Marseille Université and CNRS - homepage.
• Aleksandra Pizurica
  Department of Telecommunications and Information Processing at Ghent University - homepage.
• Christine De Mol
  Department of Mathematics and ECARES (European Center for Advanced Research in Economics and Statistics) at Brussels Free University - homepage.
• Christophe De Vleeschouwer
  Institute of Information and Communication Technologies, Electronics and Applied Mathematics at Université catholique de Louvain - homepage.

 
 

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CfP: 1st Workshop on SPARSITY AND COMPRESSIVE SENSING IN MULTIMEDIA, July 15, 2016 - Seattle, USA

 

 

Here is a new CfP as posted on the G+ group:

1st Workshop on SPARSITY AND COMPRESSIVE SENSING IN MULTIMEDIA


An IEEE ICME 2016 workshop - July 15, 2016 - Seattle, USA

Organizing committee

• Petros Boufounos (MERL, USA)
• Enrico Magli (Politecnico di Torino, Italy)

Scope
Technology improvements in multimedia content generation have led to a continuous cycle of creation, processing, communication and consumption of information as part of our social interactions and entertainment. This has spurred the development of efficient ways to acquire, process, communicate and store vast amounts of data. One of the most prominent recent breakthroughs is the development of compressed sensing and sparse representations. To-date these techniques have had significant success in numerous areas of signal acquisition, parameter estimation, communication, and machine learning. These developments have found a home in a number of applications, including media retrieval, radar and medical imaging systems, and video compression, just to mention a few.


This workshop’s objective is to bring together leading researchers around the world to present their newest accomplishments, exchange latest experiences, and explore future directions in the important and evolving fields of CS and sparse representations. In particular, it is focused on the dissemination of recent results in multimedia methods and applications that take advantage of these techniques.


We are inviting original submission to this workshop in the form of full-length 6-pages papers, or short 2-pages position papers (these latter are not going to be published in the proceedings). Topics of interest include, but are not restricted to:

• Theoretical aspects of compressive sensing and sparsity
• Communication and networking applications
• CS and sparsity for 5G communication systems
• CS and sparsity for big data
• CS and sparsity for media retrieval
• CS and sparsity for speech, audio, image and video compression
• CS and sparsity for detection, estimation and machine learning
• Compressive imaging
• Distributed applications of compressive sensing
• Emerging applications of CS and sparsity  

 

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CfP: The 3rd International Workshop on High Dimensional Data Mining (HDM’15)

Here is an interesting workshop organized by Ata Kaban

 

The 3^rd International Workshop on High Dimensional Data Mining (HDM’15)
In conjunction with the IEEE International Conference on Data Mining (IEEE ICDM 2015)

14 November 2015, Atlantic City, NJ, USA.

Description of Workshop

Over a decade ago, Stanford statistician David Donoho predicted that the 21st century will be the century of data. "We can say with complete confidence that in the coming century, high-dimensional data analysis will be a very significant activity, and completely new methods of high-dimensional data analysis will be developed; we just don't know what they are yet." -- D. Donoho, 2000.

Unprecedented technological advances lead to increasingly high dimensional data sets in all areas of science, engineering and businesses. These include genomics and proteomics, biomedical imaging, signal processing, astrophysics, finance, web and market basket analysis, among many others. The number of features in such data is often of the order of thousands or millions - that is much larger than the available sample size.

For a number of reasons, classical data analysis methods inadequate, questionable, or inefficient at best when faced with high dimensional data spaces:

 1. High dimensional geometry defeats our intuition rooted in low dimensional experiences, and this makes data presentation and visualisation particularly challenging.

 2. Phenomena that occur in high dimensional probability spaces, such as the concentration of measure, are counter-intuitive for the data mining practitioner. For instance, distance concentration is the phenomenon that the contrast between pair-wise distances may vanish as the dimensionality increases.

3. Bogus correlations and misleading estimates may result when trying to fit complex models for which the effective dimensionality is too large compared to the number of data points available.

 4. The accumulation of noise may confound our ability to find low dimensional intrinsic structure hidden in the high dimensional data.

 5. The computation cost of processing high dimensional data or carrying out optimisation over a high dimensional parameter spaces is often prohibiting.

Topics

This workshop aims to promote new advances and research directions to address the curses and uncover and exploit the blessings of high dimensionality in data mining. Topics of interest include all aspects of high dimensional data mining, including the following:

- Systematic studies of how the curse of dimensionality affects data mining methods

- Models of low intrinsic dimension: sparse representation, manifold models, latent structure models, large margin, other?

- How to exploit intrinsic dimension in optimisation tasks for data mining?

- New data mining techniques that scale with the intrinsic dimension, or exploit some properties of high dimensional data spaces

- Dimensionality reduction

- Methods of random projections, compressed sensing, and random matrix theory applied to high dimensional data mining and high dimensional optimisation

- Theoretical underpinning of mining data whose dimensionality is larger than the sample size

- Classification, regression, clustering, visualisation of high dimensional complex data sets

- Functional data mining

- Data presentation and visualisation methods for very high dimensional data sets

- Data mining applications to real problems in science, engineering or businesses where the data is high dimensional

Paper submission

High quality original submissions are solicited for oral and poster presentation at the workshop. Papers should not exceed a maximum of 8 pages, and must follow the IEEE ICDM format requirements of the main conference. All submissions will be peer-reviewed, and all accepted workshop papers will be published in the proceedings by the IEEE Computer Society Press. Submit your paper here.

Important dates

Submission deadline: July 20, 2015.

Notifications to authors: September 1, 2015.

Workshop date: November 13, 2015.

Program committee

Arthur Zimek – Ludwig-Maximilians-Universitaet, Muenchen, Germany

Ata Kaban – University of Birmingham, UK

Barbara Hammer – University of Bielefeld, Germany

Bob Durrant – Waikato University, NZ

John A. Lee – Universite Catholique de Louvain, Belgium

Mark Last – Ben-Gurion University of the Negev, Israel

Mehmed Kantardzic – University of Louisville, USA

Michael E. Houle – National Institute of Informatics, Japan
Milos Radovanovic – University of Novi Sad, Serbia

Nenad Tomasev – Google, Mountain View, CA, USA

Peter Tino – University of Birmingham, UK

Stephan Gunnemann – Carnegie Mellon University, USA

Udo Seiffert – Fraunhofer IFF Magdeburg & University of Magdeburg, Germany

Yiming Ying – SUNY, NY, USA

Workshop organisation & contact

Dr. Ata Kaban

School of Computer Science, University of Birmingham, UK

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Two Conferences: MMMA-2015, Moscow, August 2015 and CfP RSL-CV 2015, Santiago, Chile, Dec. 2015

Two meetings of interest:

Ivan just sent me the following:

Dear Igor,


we are organizing the 4-th international conference in Moscow on Matrices in Mathematics and Applications (MMMA-2015) http://matrix.inm.ras.ru/mmma-2015/ . Low-rank approximation of matrices and tensors will be the core topic of many talks.

I think it might be interesting to the readers of your blog. It is also a good time to visit Russia, since it is not very expensive now.

With best wishes,
Ivan Oseledets 

Thanks Ivan !

Andrews also sent me the following:

Hi Igor,

I'd like to forward you this call for paper for workshop on robust subspace learning and computer vision.

Best regards,

Andrews

Call for Paper for Workshop on

Robust Subspace Learning and Computer Vision (RSL-CV 2015)

Santiago, Chile, in conjunction with ICCV 2015 (http://pamitc.org/iccv15/)

Recent research on robust subspace learning and tracking by decomposition into low-rank plus additive matrices provides a suitable framework for computer vision applications such as video coding, key frame extraction, hyper-spectral video processing, dynamic MRI, motion saliency detection and background/foreground separation. In this context, decomposition into low rank plus sparse matrices has been developed in different formulation problems such as robust principal component analysis, robust non-negative matrix factorization, robust matrix completion, subspace tracking, and low-rank minimization
The aim of RSL-CV 2015 (http://rsl-cv2015.univ-lr.fr/workshop/) are three-fold: 1) proposing robust subspace learning and tracking for computer vision applications, 2) proposing new adaptive and incremental algorithms for robust subspace learning and tracking to reach the requirements of real-time applications such as background/foreground separation, motion saliency and video coding, and 3) proposing robust algorithms to tackle key challenges in applications such as dynamic backgrounds and illumination changes for background/foreground separation.
IMPORTANT DATES
Intention to Submit (not mandatory):           June 30, 2015 (with a tentative title to send to tbouwman@univ-lr.fr)
Full Paper Submission Deadline:                   September 1, 2015 (for papers not submitted at ICCV)
                                                                      September 10, 2015 (for papers that are awaiting for ICCV decisions)
Decisions to Authors:                                    October 1, 2015
Camera-ready Deadline:                               October 16, 2015

MAIN ORGANIZERS
Thierry Bouwmans, Laboratoire MIA, Univ. La Rochelle, France.
Paul Rodriguez, DSP / DIP Laboratory, Pontificia Universidad Católica del Perú. Peru.
Namrata Vaswani, Iowa State University. USA.
Brendt Wohlberg, Los Alamos National Laboratory, USA.
John Wright, Department of Electrical Engineering, Columbia University, USA.
El-Hadi Zahzah, Laboratoire L3I, Univ. La Rochelle, France.

PROGRAM COMMITTEE (To be completed)
Necdet Serhat Aybat, Pennsylvania State University, USA
Jun He, Nanjing University of Information Science and Technology, China
Soon Ki Jung, Kyungpook National University, Korea
Shiqian Ma, Chinese University of Hong Kong, China

Gonzalo Mateos, Univ. of Rochester, USA 

Lucia Maddalena, National Research Council, Italy
Shinichi Nakajima, Technische Universität Berlin, Germany
Fatih Porikli, NICTA and Australian National University, Australia
Caifeng Shan, Philips Research, The Netherlands (To be confirmed)
Xianbiao Shu, Qualcomm, San Diego, USA

PUBLICATIONS
Accepted papers will be published in the ICCV 2015 Workshop Proceedings. Selected papers, after extensions and further revisions, will be published in a special issue in an international journal.

Thanks Andrews !

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ICML 2015 papers are out

The proceedings for ICML 2015 which is to take place in Lille, is out. Here is a small sample of papers that we mentioned before or are of interest to the general themes covered on Nuit Blanche:

Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing

Rongda Zhu, Quanquan Gu

[abs] [pdf]

A Nearly-Linear Time Framework for Graph-Structured Sparsity

Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

[abs] [pdf] [supplementary]

Large-scale log-determinant computation through stochastic Chebyshev expansions

Insu Han, Dmitry Malioutov, Jinwoo Shin

[abs] [pdf] [supplementary]

Compressing Neural Networks with the Hashing Trick

Wenlin Chen, James Wilson, Stephen Tyree, Kilian Weinberger, Yixin Chen

[abs] [pdf]

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization

Jiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi

[abs] [pdf] [supplementary] 

Learning Word Representations with Hierarchical Sparse Coding

Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah Smith

[abs] [pdf] [supplementary] 

Theory of Dual-sparse Regularized Randomized Reduction

Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

[abs] [pdf] 

Streaming Sparse Principal Component Analysis

Wenzhuo Yang, Huan Xu

[abs] [pdf] [supplementary] 

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization

Jiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi

[abs] [pdf] [supplementary] 

Inferring Graphs from Cascades: A Sparse Recovery Framework

Jean Pouget-Abadie, Thibaut Horel

[abs] [pdf] [supplementary] 

Swept Approximate Message Passing for Sparse Estimation

Andre Manoel, Florent Krzakala, Eric Tramel, Lenka Zdeborovà

[abs] [pdf] 

Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization

Tyler Johnson, Carlos Guestrin

[abs] [pdf] [supplementary]

Sparse Variational Inference for Generalized GP Models

Rishit Sheth, Yuyang Wang, Roni Khardon

[abs] [pdf] 

A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data

Yining Wang, Yu-Xiang Wang, Aarti Singh

[abs] [pdf] [supplementary] 

Geometric Conditions for Subspace-Sparse Recovery

Chong You, Rene Vidal

[abs] [pdf] [supplementary]

Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix

Roger Grosse, Ruslan Salakhudinov

[abs] [pdf]

Sparse Subspace Clustering with Missing Entries

Congyuan Yang, Daniel Robinson, Rene Vidal

[abs] [pdf] 

Theory of Dual-sparse Regularized Randomized Reduction

Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

[abs] [pdf] 

Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares

Garvesh Raskutti, Michael Mahoney

[abs] [pdf]

The Power of Randomization: Distributed Submodular Maximization on Massive Datasets

Rafael Barbosa, Alina Ene, Huy Nguyen, Justin Ward

[abs] [pdf] [supplementary]

A Unified Framework for Outlier-Robust PCA-like Algorithms

Wenzhuo Yang, Huan Xu

[abs] [pdf] [supplementary] 

Streaming Sparse Principal Component Analysis

Wenzhuo Yang, Huan Xu

[abs] [pdf] [supplementary]

A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate

Ohad Shamir

[abs] [pdf] [supplementary] 

Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA

Bo Xin, David Wipf

[abs] [pdf] 

A Unified Framework for Outlier-Robust PCA-like Algorithms

Wenzhuo Yang, Huan Xu

[abs] [pdf] [supplementary]

Stay on path: PCA along graph paths

Megasthenis Asteris, Anastasios Kyrillidis, Alex Dimakis, Han-Gyol Yi, Bharath Chandrasekaran

[abs] [pdf] [supplementary] 

Deep Learning with Limited Numerical Precision

Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan

[abs] [pdf]

Training Deep Convolutional Neural Networks to Play Go

Christopher Clark, Amos Storkey

[abs] [pdf]

 

Harmonic Exponential Families on Manifolds

Taco Cohen, Max Welling

[abs] [pdf] [supplementary]

 

Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)

Andrew Wilson, Hannes Nickisch

[abs] [pdf]

Learning Deep Structured Models

Liang-Chieh Chen, Alexander Schwing, Alan Yuille, Raquel Urtasun

[abs] [pdf]

Scalable Deep Poisson Factor Analysis for Topic Modeling

Zhe Gan, Changyou Chen, Ricardo Henao, David Carlson, Lawrence Carin

[abs] [pdf] [supplementary]

Scalable Bayesian Optimization Using Deep Neural Networks

Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat, Ryan Adams

[abs] [pdf]

Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, Surya Ganguli

[abs] [pdf]

A Deeper Look at Planning as Learning from Replay

Harm Vanseijen, Rich Sutton

[abs] [pdf]

Credit: Dawn RC3 Image 20

This image of Ceres is part of a sequence taken by NASA's Dawn spacecraft on May 7, 2015, from a distance of 8,400 miles (13,600 kilometers).
Image credit: NASA/JPL-Caltech/UCLA/MPS/DLR/IDA

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