Adventures in Signal Processing and Open Science

international Traveling Workshop on Interactions between Sparse models and Technology

international Traveling Workshop on Interactions between Sparse models and Technology

On the 24th to 26th of August 2016, we are organising a workshop called international Traveling Workshop on Interactions between Sparse models and Technology (iTWIST). iTWIST is a biennial workshop organised by a cross-European committee of researchers and academics on theory and applications of sparse models in signal processing and related areas. The workshop has so far taken place in Marseille, France in 2012 and in Namur, Belgium in

I was very excited to learn last fall that the organising committee of the previous two instalments of the workshop had the confidence to let Morten Nielsen and me organise the workshop in Aalborg (Denmark) in 2016.


This year, the workshop continues many of the themes from the first two years and adds a few new:

  • 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
  • Electronic/optical compressive sensors (hardware)

I would like to point out here, as Igor Carron mentioned recently, that HW designs are also very welcome at the workshop – it is not just theory and thought experiments. We are very interested in getting a good mix between theoretical aspects and applications of sparsity and related techniques.

Keynote Speakers

I am very excited to be able to present a range of IMO very impressive keynote speakers covering a wide range of themes:

  • 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 and Eric Tramel – ENS Paris – homepage
  • Phil Schniter – Ohio State University – homepage
  • Karin Schnass – University of Innsbruck – homepage
  • Rachel Ward – University of Texas at Austinhomepage
  • Bogdan Roman – University of Cambridge – homepage

The rest of the workshop is open to contributions from the research community. Please send your papers (in the form of 2-page extended abstracts – see details here). Your research can be presented as an oral presentation or a poster. If you prefer, you can state your preference (paper or poster) during the submission process, but we cannot guarentee that we can honour your request and reserve the right to assign papers to either category in order to put together a coherent programme. Please note that we consider oral and poster presentations equally important – poster presentations will not be stowed away in a dusty corner during coffee breaks but will have one or more dedicated slots in the programme!

Open Science

In order to support open science, we strongly encourage authors to publish any code or data accompanying your paper in a publicly accessible repository, such as GitHub, Figshare, Zenodo etc.

The proceedings of the workshop will be published in arXiv as well as SJS in order to make the papers openly accessible and encourage post-publication discussion.

Compressed Sensing – and more – in Python

Compressed Sensing – and more – in Python

The availability of compressed sensing reconstruction algorithms for Python has so far been quite scarce. A new software package improves on this situation. The package PyUnLocBox from the LTS2 lab at EPFL is a convex optimisation toolbox using proximal splitting methods. It can, among other things, be used to solve the regularised version of the LASSO/BPDN optimisation problem used for reconstruction in compressed sensing:

\underset{x}{\mathrm{argmin}} \| Ax - y \|_2 + \tau \| x \|_1


Heard through Pierre Vandergheynst.

I have yet to find out if it also solves the constrained version. Update: Pierre Vandergheynst informed me that the package does not yet solve the constrained version of the above optimisation problem, but it is coming:

\underset{x}{\mathrm{argmin}} \quad \| x \|_1 \\ \text{s.t.} \quad \| Ax - y \|_2 < \epsilon

Standalone peer review platforms

Standalone peer review platforms

I have previously mentioned some platforms for open / post-publication peer review in Open Review of Scientific Literature and discussed the roles of such platforms in Third-party review platforms. I just wanted to mention the above document in Google Docs which seems to have been started by Jason Priem(?). The document contains a list of peer review platforms; both standalone and including manuscript publishing as well. Go have a look – there are probably some that you don’t know yet. Anyone can edit the document, so please add platforms if you now any additional ones. acquires Plasmyd to bring peer review into the 21st century acquires Plasmyd to bring peer review into the 21st century

I noticed this news piece today. I have previously written about open peer review platform. Most of the recent initiatives in open peer review are entirely new platforms that provide the mechanics to get open peer review going, but in my opinion a challenge for them is to attract a critical mass of users.’s move seems a bit the other way around: they already have an existing science-related platform with a quite a few users, but now they are adding peer review functionality. It is not entirely clear to me whether this means open review, but the mechanism they describe could help address the challenge of how to attract sufficient numbers of qualified reviewers to such a platform. The article does hint at the possibility that might try to “build a reveue model around their modern approach to peer review”. I am not a fan of such a model, as this is one of the things that are wrong with the traditional journal publishing model. Nevertheless, it is going to be interesting to see how it goes.

More on anonymity in peer review

This study lacked an appropriate control group: Two stars

I came across this post on anonymity in peer review by Jon Brock. I have previously tried to discuss pros and cons of anonymity here. I think Jon’s post is a quite good argument in favour of identifying reviewers.

In relation to this, I actually wanted to sign a review I did recently for a journal as I wanted to personally stand by my assessment of the manuscript. I asked with the editor first if this was OK with him. He explicitly requested me NOT to do so, because this was against their review policy…

Science Publishing Laboratory

Science Publishing Laboratory

Browsing on Twitter, I just stumbled on this blog by Alexander Grossmann. It looks like he has a ton of interesting reading on open scientific publishing. I found it through Giuseppe Gangarossa on Twitter.

An emerging consensus for open evaluation: 18 visions for the future of scientific publishing

An emerging consensus for open evaluation: 18 visions for the future of scientific publishing

I just found this treasure trove of papers on open evaluation in science thanks to this post by Curt Rice that sums it all up very well: Open Evaluation: 11 sure steps – and 2 maybes – towards a new approach to peer review

A look at the process of submitting articles to OA journals | Open Science

A look at the process of submitting articles to OA journals | Open Science.

If you are thinking of publishing your article in an open access model, there are usually two paths to choose from. One – you can publish in Green OA, which means adding the paper to a specially prepared repository (self-archiving). Two – you can choose the Gold OA model and submit your article to an OA journal, where it will be corrected, peer-reviewed then published. At this point I would like to briefly describe the process of submitting articles to OA journals for those who are considering just that option. It is a general description, and various steps may differ depending on the publisher and the journal.

DAT versioned data

DAT versioned data

I just came across this presentation shared by Karthik Ram on Twitter (see also It describes a project that tries to create a sort of git for data. It seems to be at a very early stage yet, but looks very interesting.

Modern LaTeX Usage

Modern LaTeX Usage
Fork me on GitHub

I have put a small LaTeX presentation online. I am quite sure the title is going to attract some corrections from readers that know how to do things better; you are very welcome – bring ’em on.

It was put together for a presentation at an internal meeting in my research group and the title was deliberately chosen to provoke feedback from my colleagues. It is not intended as a complete introduction to LaTeX – just an overview of some useful ways and packages to do certain things. You can share and edit it as you like, it is CC-BY-licensed. You can clone the source from GitHub.

Forest Vista

seeking principles

Academic Karma

Re-engineering Peer Review

Pandelis Perakakis

experience... learn... grow


computing with space | open notebook


Peer-review is the gold standard of science. But an increasing number of retractions has made academics and journalists alike start questioning the peer-review process. This blog gets underneath the skin of peer-review and takes a look at the issues the process is facing today.

Short, Fat Matrices

a research blog by Dustin G. Mixon

Discover and manage research articles...

Science Publishing Laboratory

Experiments in scientific publishing

Open Access Button

Push Button. Get Research. Make Progress.

Le Petit Chercheur Illustré

Yet Another Signal Processing (and Applied Math) blog