News Archives

Open positions in Machine Learning, Lille (France)

We would like to advertise that tenure positions for researchers will be opened soon by the French National Research Institute for Computer Science and Control (INRIA, http://www.inria.fr/index.en.html).

In Lille, two research groups have stong interest in machine learning
* Sequel (http://sequel.futurs.inria.fr/), reinforcement learning
* Mostrare (http://mostrare.futurs.inria.fr/), structured prediction
4 positions of junior researchers and 1 position of experienced researcher will be open in Lille.
We would also like to mention that opportunities exist for:
* tenure positions for senior researchers in order to create a new research group
* five years positions for senior researchers
* postdoctoral positions
* PhD grants

A thorough description of these opportunities is given on our Web sites.

If you have any question, please get in touch with us, either remi.gilleron (at) inria.fr (Mostrare), or remi.munos (at) inria.fr, philippe.preux (at) inria.fr for SequeL.
If you want to apply, it is crucial that you get in touch with us, as early as possible.

Workshop on Advances in Machine Learning for Computational Finance: Call for Contributions

Workshop on Advances in Machine Learning for Computational Finance http://web.mac.com/davidrh/AMLCF09/

Sponsored by the PASCAL 2 Network of Excellence http://www.pascal-network.org/

CALL FOR CONTRIBUTIONS: We solicit submissions for the Advances in Machine Learning for Computational Finance workshop to be held on July 20-21, 2009 at University College London Bloomsbury Campus, London, U.K. Computational finance is a cross-disciplinary field which relies on mathematical finance, numerical methods and computer simulation to make trading, hedging and investment decision, as well as facilitating the risk management of these decisions. Machine learning is concerned with the design and development of algorithm and techniques that extract rules and patterns out of data automatically, by computational and statistical methods.

This workshop brings together researches from machine learning, computational finance, academic finance and the financial industry to discuss problems in finance where machine learning may solve challenging problems and provide an edge over existing approaches. The aim of the workshop is to promote discussion on recent progress and challenges as well as on methodological issues and applied research problems. The emphasis will be on practical problem solving involving novel algorithmic approaches.

Topics of the workshop include (but not limited to):

. *Optimisation methods
. *Reinforcement learning
. *Supervised and semi-supervised learning
. *Kernel methods
. *Bayesian estimation
. *Wavelets
. *Evolutionary computing
. *Recurrent and state space models
. *SVM’s
. *Neural networks
. *Boosting
. *Multi-agent simulation
. *….
. *High frequency data
. *Trading strategies and hedging techniques
. *Execution models
. *Forecasting
. *Volatility
. *Extreme events
. *Credit risk
. *Portfolio management and optimisation
. *Option pricing
. *…

The workshop is a core event of the PASCAL 2 EU Network of Excellence.

SUBMISSION PROCEDURE: We invite the submission of high quality extended abstracts (2 to 4 pages) in the NIPS style (http://nips.cc/PaperInformation/StyleFiles). Abstracts should be sent (in .pdf/.ps/.doc) to the organisers (D.Hardoon@cs.ucl.ac.uk , l.zangeneh@cs.ucl.ac.uk). A selection of the submitted abstracts will be accepted as either an oral presentation or poster presentation.

IMPORTANT DATES:

23 Feb 09 – Submission deadline for extended abstracts
30 Mar 09 – Notification of acceptance
20-21 Jul 09 – Workshop at UCL, London, U.K.

CONFIRMED INVITED PASCAL SPEAKERS:
David Cliff
University of Bristol

Vince Darley
Eurobios

Vasant Dhar
New York University, Stern School of Business

László Györfi
Budapest University of Technology and Economics

Michael Kearns
University of Pennsylvania

David Leinweber
University of Berkeley, Haas School of Business

ORGANISERS

David R. Hardoon – University College London
John Shawe-Taylor – University College London
Philip Treleaven -University College London
Laleh Zangeneh – University College London

PROGRAM COMMITTEE

Nicolò Cesa-Bianchi – Università degli Studi di Milano
Ran El-Yaniv – Technion – Israel Institute of Technology
Samet Gogus – Barclaycard
Yuri Kalnishkan – Royal Holloway, University of London
Jasvindor Kandola – Merrill Lynch
Donald Lawrence – University College London
Giuseppe Nuti – Deutsche Bank
Sandor Szedmak – University of Southampton
Chris Watkins – Royal Holloway, University of London

Master/PhD position at INRIA Grenoble / ETH Zurich

The LEAR research group at INRIA Grenoble and the CALVIN research group at the Computer Vision Laboratory of ETH Zurich are looking for a Master and/or PhD student. The candidate will be jointly supervised and will spend time in both institutions (http://lear.inrialpes.fr/ and http://www.vision.ee.ethz.ch/).

Topic: Exploiting associations between text and images will become more and more important over the next few years to reduce the amount of manual annotation necessary to learn visual concepts. Existing work has mainly focused on associating either nouns to image regions [1], or names to faces [2,3]. While techniques for associating nouns to regions require annotated image-nouns pairs, works on names and faces use uncontrolled News captions collected from the internet. However, their success depends heavily on the availability of a pre-trained face detector. In the case of general object classes, such detectors are a central component of what the system should learn automatically. The main goal of this project is to generalize existing approaches so that generic object classes can be learned from image-caption pairs mined from the internet. A possible research avenue is to devise techniques for bootstrapping background knowledge from supervised data, and then automatically move up to less and less supervision. Another important direction is to go beyond individual nouns and explore relations between multiple words, especially words of different types, such as nouns-adjectives and names-verbs. The visual counterparts of adjectives and verbs are attributes [5,6,7] and poses/actions [8,9] respectively. Relational words such as prepositions and comparators [4] could also be incorporated, as well as larger structures composed of more than two words. The multi-entity nature of the project also opens the door to the exciting possibility of automatic learning context models. The project is part of a larger research endeavor to model the parallel between the structure of visual scenes and the structure of natural sentences.

Your profile:
* Bachelor/Masters degree (preferably in Computer Science or Applied Mathematics; Electrical Engineering will also be considered)
* Solid programming skills; the project involves programming in Matlab and C++
* Solid mathematics knowledge (especially linear algebra and statistics)
* Creative and highly motivated
* Fluent in English, both written and spoken
* Prior knowledge in the areas of computer vision, machine learning or data mining is a plus (ideally a Bachelor/master thesis in a related field)

Duration: 6 to 9 month (Masters) or 3 years (PhD)

Start date: As soon as possible

Location: This is a joint project between INRIA Grenoble and ETH Zurich. The candidate will be required to spend time in both institutions.

Contacts:
Res. Dir. Cordelia Schmid, schmid (at) inrialpes.fr
Prof. Vittorio Ferrari, ferrari (at) vision.ee.ethz.ch

Please send applications via email, including:
* a complete CV
* graduation marks
* topic of your Bachelor/master thesis
* the name and email address of two references (including your BS/master thesis supervisor)
* if you already have research experience, please include a publication list and references

Literature:
[1] K. Barnard, P. Duygulu, N. de Freitas, D. Forsyth, D. Blei, and M. Jordan, Matching Words and Pictures, JMLR 2003
[2] T. Berg, A. Berg, J. Edwards, M. Maire, R. White, Y. Teh, E. Learned-Miller, D. Forsyth, Names and Faces in the News, CVPR 2004
[3] M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid, Automatic Face Naming with Caption-based Supervision, CVPR 2008
[4] A. Gupta and L. Davis, Beyond Nouns: Exploiting Prepositions and Comparators for Learning Visual Classifiers, ECCV 2008
[5] V. Ferrari and A. Zisserman, Learning Visual Attributes, NIPS 2007
[6] K. Yanai and K. Barnard, Image Region Entropy: A Measure of “Visualness” of Web Images Associated with One Concept, ACM Multimedia 2005
[7] J. Van de Weijer, C. Schmid, and J. Verbeek, Learning Color Names from Real-World Images, CVPR 2007
[8] V. Ferrari, M. Marin-Jiminez, and A. Zisserman, Progressive Search Space Reduction for Human Pose Estimation, CVPR 2008
[9] I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, Learning Realistic Human Actions from Movies, CVPR 2008.

PhD Scholarship in Non-Invasive BCI at EPFL

EPFL, one of the two Swiss Federal Institutes of Technology (http://www.epfl.ch), has immediate openings for four PhD students in the field of brain-computer interaction (BCI) to work in the lab of Prof. José del R. Millán (http://people.epfl.ch/jose.millan). Millán’s lab conducts research on non-invasive BCI and neuroprosthetics. His lab is part of the newly-launched Center for Neuroprosthetics (http://actualites.epfl.ch/presseinfo-com?id=661&newlang=eng), which carries out research at the interface of neuroscience and bioengineering in an environment of both theoretical and experimental research, rich for the development of novel enabling technologies as well as for seeking deeper understanding of fundamental mechanisms underlying the field of neuroprosthetics.

The successful candidates will work in the framework of European and Swiss projects related to the development of novel non-invasive BCI for multimodal interaction. They will also investigate the underlying machine learning and signal processing principles for robust recognition of different cognitive processes.

The candidates should have a masters degree (or equivalent) in computer science, electrical engineering, biomedical engineering, or related fields. She or he should have good background in statistical machine learning, signal processing, EEG analysis, and/or human-machine interaction, and/or intelligent/adaptive robotics. Excellent programming skills are a must. Candidates must also have a good command of spoken/written English language. The positions are available immediately and will remain open until suitable candidates are found. Starting date is February 1, 2009, or at the earliest convenience afterwards.

Application: Interested candidates should send a short letter of motivation, a detailed CV, and names of 3 references to Prof. José del R. Millán (jose.millan AT epfl.ch).

Postdoc Openings in Non-Invasive BCI at EPFL

EPFL, one of the two Swiss Federal Institutes of Technology (http://www.epfl.ch), has immediate openings for one postdoc in the field of brain-computer interaction (BCI) to work in the lab of Prof. José del R. Millán (http://people.epfl.ch/jose.millan). Millán’s lab conducts research on non-invasive BCI and neuroprosthetics. His lab is part of the newly-launched Center for Neuroprosthetics (http://actualites.epfl.ch/presseinfo-com?id=661&newlang=eng), which carries out research at the interface of neuroscience and bioengineering in an environment of both theoretical and experimental research, rich for the development of novel enabling technologies as well as for seeking deeper understanding of fundamental mechanisms underlying the field of neuroprosthetics.

The successful candidates will work in the framework of European and Swiss projects related to the development of novel non-invasive BCI for neuroprosthetics. They will also investigate the underlying machine learning and signal processing principles for robust recognition of different cognitive processes.

The candidates should have a PhD in computer science, electrical engineering, biomedical engineering, cognitive neuroscience or related fields. She or he should have good background in statistical machine learning, signal processing, EEG analysis, human-machine interaction, and/or intelligent/adaptive robotics. Excellent programming skills are a must. Candidates must also have a good command of spoken/written English language. The positions are available immediately and will remain open until a suitable candidate is found. Starting date is February 1, 2009, or at the earliest convenience afterwards.

Application: Interested candidates should send a short letter of motivation, a detailed CV, and names of 3 references to Prof. José del R. Millán (jose.millan AT epfl.ch).

Workshop on Sparsity in Machine Learning and Statistics – Call for Papers

============================================
Workshop on Sparsity in Machine Learning and Statistics

Cumberland Lodge, UK
1 – 3 April 2009

http://www.cs.ucl.ac.uk/staff/rmartin/smls09/

CALL FOR PAPERS
============================================

Sparse estimation is playing an increasingly important role in the statistics and machine learning communities. Several methods have recently been developed in both fields, which rely upon the notion of sparsity (e.g.penalty methods like the Lasso, the Winnow algorithm, linear programming boosting, Dantzig selector, etc.), which can be thought of as a mathematical version of Occam’s razor. Many of the key theoretical ideas and statistical analysis of the methods have been developed independently, but there is increasing awareness of the potential for cross-fertilization of ideas between statistics and machine learning. Sparse estimation is starting to have an important impact on applied areas also, with applications ranging from biostatistics, medical imaging, to geoscience and finance. To bring together results on sparsity from different applied and theoretical fields of machine learning and statistics, we are planning to hold a workshop on 1-3rd April 2009 at Cumberland Lodge, UK.

The Invited Speakers include:
– Nicolò Cesa-Bianchi (Università degli Studi di Milano),
– Sara van de Geer (TBC) (ETH Zurich),
– Charles Micchelli (TBC) (State University of New York)
– Jared Tanner (University of Edinburgh),
– Alexandre Tsybakov (CREST and Université Paris VI),
– Jon Wellner (University of Washington),
– David Wipf (University of California),
– Ming Yuan (Georgia Tech College of Engineering),

and each invited speaker will give an hour long presentation, on different aspects of sparse estimation. In addition to the invited lectures there will be a number of contributed presentations, and a poster session. We invite you to submit a full page extended abstract, with pointers to reference material where appropriate. Submissions should be sent to smls2009@gmail.com and should be received by Thursday 15 January 2009. Notification of acceptance will be given on Friday 30 January 2009.

See also http://www.cs.ucl.ac.uk/staff/rmartin/smls09/

Papers will be selected for oral or poster presentation.

Sofia Olhede, Massimiliano Pontil & John Shawe-Taylor

The GREAT08 Challenge

Will you be taking up the GRavitational lEnsing Accuracy Testing 2008
(GREAT08) PASCAL Challenge? The GREAT08 Challenge is an image analysis competition for gravitational lensing and cosmology, aimed at experts in statistical problems (including non-astronomers).

You can find more information here
http://www.great08challenge.info
http://www.sciencemag.org/content/vol322/issue5902/s-scope.dtl
http://cs.astronomy.com/asycs/blogs/astronomy/2008/10/29/cosmologists-issue-challenge.aspx
There will be a videocon workshop on Monday 5th January 1-6pm GMT which will include an introduction to GREAT08.

Please sign up to the mailing list to receive important information by entering your address in the box at http://www.great08challenge.info

If you have any questions then please contact me, or another member of the GREAT08 Team on questions@great08challenge.info

The GREAT08 Team

Post doctoral position in Machine Learning/Cognitive Vision/CBIR

For a project funded by the Austrian Science Foundation (FWF) and the European Commission, we are looking for a highly motivated post doctoral researcher with background in machine learning and/or cognitive vision and/or content based image retrieval. Among the possible fields of specialization are on-line learning, active learning, reinforcement learning, visual object classification, relevance feedback, and query-by-example search.

To learn more about the above project and the research at the Chair of Information Technology, University of Leoben, Austria, please visit http://institute.unileoben.ac.at/infotech.

This position will be filled in January 2009 for the duration of 2 years (with a possible extension). Depending on your qualification salary is 30000-45000 EUR per year (after paying all social and insurance benefits and taxes this is net 1500-2000 EUR per month). Highly qualified PhD candidates may be considered as well.

Applicants should submit 1) a CV, including a brief research statement,
2) 1-3 recent publications in electronic format, and 3) the names and contact information of three individuals who can serve as references.

Contact:

Univ.-Prof. Dr. Peter Auer
University of Leoben
Chair for Information Technology
Franz-Josef-Strasse 18, A-8700 Leoben, Austria
Fax: +43(3842)402-1502
E-mail: auer (at) unileoben.ac.at

PASCAL Newsletter

The PASCAL newsletter contains all the latest updates, plus links to recently added publications and upcoming events.

Image
December 2008

Junior Research Groups (W1/W2), Saarland University, Saarbruecken

Saarland University is seeking to establish several

Junior Research Groups (W1/W2)

within the recently established Cluster of Excellence “Multimodal Computing and Interaction” which was established by the German Research Foundation (DFG) within the framework of the German Excellence Initiative.

The term “multimodal” describes the different types of digital information such as text, speech, images, video, graphics, and high-dimensional data, and the way it is perceived and communicated, particularly through vision, hearing, and human expression. The challenge is now to organize, understand, and search this multimodal information in a robust, efficient and intelligent way, and to create dependable systems that allow natural and intuitive multimodal interaction. We are looking for highly motivated young researchers with a background in the research areas of the cluster, including algorithmic foundations, secure and autonomous networked systems, open science web, information processing in the life sciences, visual computing, large-scale virtual environments, synthetic virtual characters, text and speech processing and multimodal dialog systems. Additional information on the Cluster of Excellence is available on http://www.m2ci.org. Group leaders will receive junior faculty status at Saarland University, including the right to supervise Bachelor, Master and PhD students. Positions are limited to five years.

Applicants for W1 positions (phase I of the program) must have completed an outstanding PhD. Upon successful evaluation after two years, W1 group leaders are eligible for promotion to W2. Direct applicants for W2 positions (phase II of the program) must have completed a postdoc stay and must have demonstrated outstanding research potential and the ability to successfully lead their own research group. Junior research groups are equipped with a budget of 80k to 100k Euros per year to cover research personnel and other costs.

Saarland University has leading departments in computer science and computational linguistics, with more than 200 PhD students working on topics related to the cluster (see http://www.informatik-saarland.de for additional information). The German Excellence Initiative recently awarded multi-million grants to the Cluster of Excellence “Multimodal Computing and Interaction” as well as to the “Saarbrücken Graduate School of Computer Science”. An important factor to this success were the close ties to the Max Planck Institute for Computer Science, the German Research Center for Artificial Intelligence (DFKI), and the Max Planck Institute for Software Systems, which are co-located on the same campus.

Candidates should submit their application (curriculum vitae, photograph, list of publications, short research plan, copies of degree certificates, copies of the five most important publications, list of five references) to the coordinator of the cluster, Prof. Hans-Peter Seidel, MPI for Computer Science, Campus E1 4, 66123 Saarbrücken, Germany. Please, also send your application as a single PDF file to applications@mmci.uni-saarland.de.

The review of applications will begin on January 15, 2009, and applicants are strongly encouraged to submit applications by that date; however, applications will continue to be accepted until January 31, 2009. Final decisions will be made following a candidate symposium that will be held during March 9 – 13, 2009.

Saarland University is an equal opportunity employer. In accordance with its policy of increasing the proportion of women in this type of employment, the University actively encourages applications from women. For candidates with equal qualification, preference will be given to people with physical disabilities.