PhD scholarship at INRIA – LEAR research group in Grenoble, http://lear.inrialpes.fr

Topic: The goal of this PhD is to better understand videos by exploiting associated textual data. For still images some success has been achieved in learning correspondences between objects and textual keywords [1]. In video, it has been demonstrated that transcripts aligned with the video can be a very useful source of weak supervision for learning the appearance of characters [2] and human actions [3].
Existing work does not attempt to use text as a form of supervision for learning spatio-temporal constraints between scenes, humans, objects and their interactions in video. In addition, the text is typically considered as a supervisory signal for visual learning and the opposite direction, where visual information would help disambiguate text interpretation, is not considered. In this PhD, we propose to go beyond the state-of-the-art and turn textual annotations into a more complete and accurate supervisory signal for the different stages of the scene/object/human action interpretation process. In particular, we want to develop spatio-temporal correspondences between videos and the available text annotations, and exploit these correspondences as constraints for learning actions in videos.

Your profile:

* Master degree (preferably in Computer Science or Applied Mathematics; Electrical Engineering will also be considered)
* Solid programming skills; the project involves programming in 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 Master thesis in a related field)

Duration: 3-4 years

Start date: September 2012.

Location: INRIA Grenoble, France. Grenoble lies in the French Alpes and offers ideal conditions for skiing, hiking, climbing etc.

Contact: Cordelia Schmid, schmid@inria.fr

Please send applications via email, including:

* a complete CV
* graduation marks
* topic of your Master thesis
* the name and email address of two references (including your Master thesis supervisor)

Literature:

[1] M. Guillaumin, T. Mensink, J. Verbeek and C. Schmid.
International Journal of Computer Vision, 2012.

[2] M. Everingham, J. Sivic, and A. Zisserman. Taking the bite out of
automatic naming of characters in TV video. Image and Vision
Computing, 2009.

[3] O. Duchenne, I. Laptev, J. Sivic, F. Bach, and J. Ponce. Automatic
annotation of human actions in video. In International Conference on
Computer Vision, 2009.

CVMP2012 Full Paper deadline EXTENDED to 26th June.

CVMP2012 Full Paper deadline EXTENDED to 26th June. Don’t forget the Google £2k Best student paper prize this year.

If you have been doing innovative work then we’d love to hear about it. High-quality papers are invited which present novel research related to any aspect of media production. Full length submitted papers will be subject to peer review. The papers will be published in cooperation with Eurographics and ACM (pending). Selected papers will be invited (and fast-tracked) to submit extended versions to the IEEE Transactions on Multimedia. All details on the CVMP website http://www.cvmp-conference.org/

CVMP 2012 is the 9th annual industry-academic conference series on media production for film, broadcast and games. Visual media production brings together expertise in video processing, computer vision, computer graphics, animation and physical simulation. CVMP provides a forum for presentation of the latest research advances combined with key-note and invited talks on state-of-the-art industry practice in content production and post-production. CVMP is rapidly building a reputation as a prime venue for researchers to meet with image practitioners in the film and television industry. For instance, in 2011 48% of the audience were from the film and television post-production industry including representation from high profile post-houses such as Moving Picture Company, Double Negative, and so forth. Furthermore, CVMP hosts keynotes from distinguished researchers and professionals from industry (to name have few from previous years: Jeremy Doig / Google, Roberto Cipolla / Cambridge University, Sylvain Paris / Adobe).

Call for participation: PhD Summer School on Machine Learning

********************************************************************************
PhD Summer School on Machine Learning
(www.imm.dtu.dk/courses/02901)

August 13 – 17, 2012 (both days included) DTU Informatics, Technical University of Denmark
********************************************************************************

We hereby invite you to participate in the PhD Summer School on Advanced Topics in Machine Learning that will take place at the Technical University of Denmark.

The course will consist of lectures given by invited speakers with expertise in machine learning as well as members of the research groups at DTU Informatics. The course will cover key topics in machine learning including Bayesian parametric and non-parametric inference, optimization, low rank approximations and kernel methods.

Confirmed PASCAL2 invited speakers:

Aki Vehtari, Aalto University
Ryota Tomioka, University of Tokyo

Further information regarding the summer school, including list of invited speakers and program, can be found on our webpage:
www.imm.dtu.dk/courses/02901

For registration, please contact: Marian Solrun Adler masad@imm.dtu.dk

We hope to see you at the campus of the Technical University of Denmark.

The organizers,
Morten Mørup, Lars Kai Hansen, Mikkel N. Schmidt and Ole Winther

JIMSE: Joint workshop on Intelligent Methods for Software System Engineering

JIMSE: Joint workshop on Intelligent Methods for Software System Engineering
****************************************************************************

Co-located with ECAI 2012
August 27 or 28, 2012
Montpellier, France

The first Joint workshop on Intelligent Methods for Software System
Engineering will be held in conjunction with ECAI 2012, the biennial
European Conference on Artificial Intelligence, the leading conference
on Artificial Intelligence in Europe, which will take place in
Montpellier, France, in August, 27-31, 2012.

JIMSE is co-organized by the European Coordination Action EternalS:
Trustworthy Eternal Systems via Evolving Software, Data and Knowledge.

Please visit the workshop website:

https://sites.google.com/site/jimse2012/

News:

*** Submission deadline extended to June 20, 2012 ***

*** Student scholarships – application deadline June 25 ***
(for students selected based on their submitted abstract)

Important Dates
—————

*** June 20, 2012 ***: Paper submission deadline
*** June 25, 2012 ***: Student abstract deadline
July 5, 2012: Notification of acceptance
July 15, 2012: Camera-ready deadline
July 22, 2012: send PDF to workshop chairs
August 27 or 28, 2012 JIMSE workshop at ECAI 2012

Submission
———-

To promote discussion and the topics of the workshop, we invite the
submission of papers of max. 4 pages including references, pictures
and tables, presenting novel research results or position papers. The
abstracts will be peer reviewed by the Program Committee (double-blind
review process). Final versions of the extended abstracts (max. 10
pages including references) will be published in online proceedings,
while selected contributions will appear as post-proceedings in the
Springer CCIS (Communications in Computer and Information Science)
series (pending approval). For further details see
http://www.springer.com/series/7899

Students are particularly encouraged to submit an abstract of 2 to 4
pages. Submission of student abstracts regarding concrete research or
research ideas related to any of the topics above. Student abstracts
will be posted on the workshop website and a selection of them will be
awarded a scholarship to attend the workshop and ECAI.

Papers should be submitted via the Easychair submission
system:

https://www.easychair.org/conferences/?conf=jimse2012

For student abstracts, please indicate it at submission time by adding
“student abstract” to the keyword list.

All submissions should be formatted using the ECAI 2012 style file
that can be found at:

http://people.cs.kuleuven.be/~luc.deraedt/ecai2012-style.zip

As the reviewing will be blind, papers must not include the authors’
names and affiliations. Submissions should be in English and should
not have been published previously. If essentially identical papers
are submitted to other conferences or workshops as well, this fact
must be indicated at submission time.

The submission deadline is 23:59 CET on June 20, 2012 (for papers)
and June 25, 2012 (for students abstracts).

Voice your ideas
—————-

The contributions and the outcome of the discussion that will follow
the paper presentation will be considered for inclusion in the roadmap
that the EternalS coordination action is designing for the European
community: https://www.eternals.eu

The roadmap will be an input to the European Community for the definition
of the Work Programme of 2013.

Program Committee
—————–

Andreas Andreou, University of Cyprus, Cyprus
Lefteris Angelis, Aristotle University of Thessaloniki, Greece
Roberto Basili, University of Rome Tor Vergara, Italy
Helen Berki, University of Tampere, Finland
Götz Botterweck, Lero, Ireland
Sofia Cassel, University of Uppsala, Sweden
Krishna Chandramouli, Queen Mary University of London, UK
James Clarke, Telecommunications Software and Systems Group, Ireland
Anna Corazza, University of Naples Federico II, Italy
Sergio Di Martino, University of Naples Federico II, Italy
Michael Felderer, University of Innsbruck, Austria
Fausto Giunchiglia, University of Trento, Italy
Reiner Hähnle, TU Darmstadt, Germany
Falk Howar, TU Dordtmund, Germany
Valerie Issarny, INRIA, France
Richard Johansson, University of Gothenburg, Sweden
Jan Jürjens, TU Dortmund, Germany
George Kakarontzas, Technical University of Larisa, Greece
Achilles Kameas, Hellenic Open University, Greece
Basel Katt, University of Innsbruck, Austria
Chris Lokan, UNSW@ADFA, Australia
Ilaria Matteucci, CNR, Italy
Emilia Mendes, University of Auckland, Νew Zealand
Grzegorz Nalepa, AGH University of Science and Technology, Poland
Claudia Niederee, L3S Research Center Hannover, Germany
Animesh Pathak, INRIA, France
Tomas Piatrik, Queen Mary University of London, UK
Hongyang Qu, University of Oxford, UK
Rick Rabiser, JKU Linz, Austria
Vasile Rus, The University of Memphis, USA
Riccardo Scandariato, Katholieke Universiteit Leuven, Belgium
Ina Schaefer, TU Braunschweig, Germany
Holger Schöner, Software Competence Center Hagenberg, Austria
Bernhard Steffen, TU Dortmund, Germany
Christos Tjortjis, The University of Manchester, UK
Grigorios Tsoumakas, Aristotle University of Thessaloniki, Greece
Michalis Vazirgiannis, Athens University of Economics & Business
Maria Virvou, University of Piraeus, Greece
Qianni Zhang, Queen Mary University of London, UK

Workshop Chairs
—————

Stamatia Bibi (Aristotle University of Thessaloniki, Greece)
Alessandro Moschitti (University of Trento, Italy)
Barbara Plank (University of Trento, Italy)
Ioannis Stamelos (Aristotle University of Thessaloniki, Greece)

Contact & Website
—————–

For general questions about the workshop, please send an email to
jimse2012@gmail.com

Workshop website: https://sites.google.com/site/jimse2012/

Open PhD position in machine learning and signal processing at Qarma, LIF, Marseille

We are looking for candidates for a three-year funded PhD entitled “Acceleration of greedy algorithms for signal modeling – Theory and applications” at Qarma, LIF, Marseille. See offer below, also available at http://www.lif.univ-mrs.fr/~vemiya/research/PhD_offer_Greta_Qarma.pdf .
Acceleration of greedy algorithms for signal modeling – Theory and applications

PhD position

Supervisors: Valentin Emiya and Liva Ralaivola, Laboratoire d’Informatique Fondamentale de Marseille, France

This PhD position is funded for three years.

PhD description

Keywords. Algorithms, machine learning, signal processing, optimization, sparsity.

Abstract. This PhD project addresses theoretical and applicative aspects of emerging sci- entific topics at the interface between machine learning and signal processing. The goal is to design new greedy algorithms, focusing on their speed.

Scientific context. Sparse approaches can model a wide range of signals – images, sounds, biomedical signals, and so on – and their intrinsic structures. They benefit from a solid theory and efficient algorithms. These modern techniques are used in a growing number of applications such as signal compression and coding, source separation, inpainting or pattern recognition.
Goal. Today’s algorithms are limited by their computational complexity. As a result, they are slow and cannot handle large volumes of data. In practice, this is a major limitation since applications are more and more demanding e.g. in terms of real time constraints or fine 3D discretization. Recent theoretical results have opened new directions for the design of fast algo- rithms. In the case of greedy algorithms such as Matching Pursuit, preliminary theoretical and experimental results have been obtained at Laboratoire d’Informatique Fondamentale de Mar- seille (LIF). The goal of this PhD project is to develop this topic by designing new algorithms and validating them with theoretical and practical considerations. Several applications will be addressed such as audio inpainting and underwater acoustic imaging.

Tentative workflow. First, the PhD candidate will get familiar with sparse models and algorithms, and work on algorithmic ideas emerging from the preliminary results obtained at LIF. The research will be pursued in both the theoretical and the applicative direction, the focus being more on one or the other, depending on the candidate’s profile.

Collaborative context. The PhD project is at the core of a French ANR (national fund) project called
GRETA (Greediness – theory and algorithms) initiated in 2012 by LIF, LATP and INSA Rouen. The PhD candidate will work within an active research group and will have the opportunity to travel inside and outside France, for conferences and collaborations.

Supervisors: Valentin Emiya and Liva Ralaivola, Qarma team, LIF.

Team and scientific environment

The PhD candidate will join the Qarma team at Laboratoire d’Informatique Fondamentale de
Marseille, which is a joint research lab between CNRS and Aix-Marseille University. The Qarma team (about twelve researchers) dedicates its activities to statistical machine learning theory and applications to signal processing and multimedia indexing.

The PhD candidate will also work with Sandrine Anthoine, a researcher at the neighboring mathematics lab. LATP. Other scientific exchanges will be possible locally and nationally (with the partners of the GRETA project, Rémi Gribonval at INRIA Rennes, Laurent Daudet at Paris 7 University, Jacques Marchal at Paris 6 University).

Required background
The applicant must have at least one of the following profiles: maths, signal processing, machine learning, computer science.

Salary
The candidate will be hired for three years with a standard French PhD contract (contrat doc- toral). The net salary is 1374.21 euros per month including health insurance. Teaching or consulting opportunities may be added to the contract if the candidate wishes.

Application
Applicants should contact Valentin Emiya and Liva Ralaivola (firstname.lastname@lif.univ-mrs. fr) as soon as possible. Additional information about the PhD project will be available at this stage.
The application must be sent by email to Valentin Emiya and Liva Ralaivola according to the schedule below. It must include

• a cover letter explaining the applicant’s motivations,
• a resume,
• a transcript of the Master degree marks (or equivalent), • optional: recommendation letters or referees contacts.

The selected applicants will be interviewed, either in the lab or by phone.

Schedule (subject to changes):
• June 30, 2012: deadline for sending the application.
• July 10, 2012: end of the interviews and announcement of the results. • October 1st, 2012: beginning of the contract.

Contact
Valentin Emiya and Liva Ralaivola, firstname.lastname@lif.univ-mrs.fr.

PTDM-2012 Call for papers

*****************************************************************************
PTDM-2012: Call for papers

Practical Theories of Exploratory Data Mining (PTDM-2012)
https://sites.google.com/site/ptdm2012/welcome

Co-located with ICDM-2012 Brussels, Belgium (10-13 Dec 20012)
*****************************************************************************

Introduction:

The goal of this ICDM 2012 workshop is to help closing the gap between data mining practice and theory. To this end, we intend to explore what is the essence of exploratory data mining and how to formalize it in order to make it useful in practice. This workshop will survey (through invited as well as contributed talks and posters) some existing attempts at addressing the problems mentioned above. We particularly encourage papers that present principled theoretical contributions motivated by real world requirements.

We invite submissions on theoretically well-founded advances that have the potential to increase the practical impact of exploratory data mining (defined as a set of tools designed to help ‘real’ users explore ‘real’ data), by making it more powerful and user friendly. Specific topics of interest include:

• Data mining foundations.
• Unified frameworks for data mining.
• Iterative/interactive data mining.
• Relational data mining.
• Statistical and information theoretic assessment and comparison of data mining patterns/results.
• Visual representation of data mining patterns/results.
• Lessons learned from applications in Bioinformatics, Web and Social Network Analysis, Medicine, Business Analytics, Marketing, and other applications areas.

Thought-provoking and insightful position papers on these topics are welcome as well. All submissions will be subjected to a thorough review process by at least 2 and normally 3 reviewers. The overriding criteria for acceptance will be originality, promise of the ideas to ultimately enhance the impact of data mining in practice, and potential to inspire further research.

Submissions:

The format should be a maximum of 8 pages in the IEEE ICDM format (see ICDM conference website) but shorter contributions are welcome as well. The review process is single blind (reviewers unknown to the authors), so please include author names on the title page.

Authors of accepted papers will be given the opportunity to present their work in an oral presentation or poster presentation (depending on quality and suitability of the topic for oral presentation).

All accepted papers will be published in the IEEE workshop proceedings.

Important dates:

August 10, 2012: Workshop paper submission deadline
October 1, 2012: Notification of paper acceptance to authors
October 15, 2012: Camera-ready deadline for accepted papers
December 10, 2012: Workshop date

Organizers:

Tijl De Bie, Akis Kontonasios, Eirini Spyropoulou

ACL 2012 Joint Workshop on Statistical Parsing and Semantic Processing of Morphologically Rich Languages (SP-Sem-MRL 2012)

ACL 2012 Joint Workshop on Statistical Parsing and Semantic Processing of Morphologically Rich Languages (SP-Sem-MRL 2012)
https://sites.google.com/site/spsemmrl2012/

Thanks to the generous support of PASCAL, this workshop provides registration support to PASCAL students and members, and possibly, budget permitting, to other students as well. Please see REGISTRATION AND FINANCIAL SUPPORT on the workshop website for details.

Faculty Position, Machine Learning, University of Oxford

University Lecturer In Engineering Science::Information Engineering::Machine Learning

The Department of Engineering Science, University of Oxford, UK, proposes to appoint a University Lecturer in Engineering Science in the general area of Information Engineering/Machine Learning from 1st January 2013 or as soon as possible thereafter.

Although no strict restriction is placed on the specialised area of research, candidates with an interest in machine learning and its application to big-data, computer vision, robotics or signal processing are especially welcome. The department is looking to appoint an individual whose research activity will expand or complement existing strengths in machine vision, surveillance, statistical signal processing, machine learning, sensing, autonomy and robotics.

The successful candidate will work at the Department of Engineering Science and will be offered a Non-Tutorial Fellowship at Kellogg College under arrangements described in the further particulars. The appointment will be initially for five years at which point, upon completion of a successful review, the post holder will be eligible for reappointment to the retiring age. The successful candidate will have a strong background in Information Engineering, including a doctorate.

Candidates should have a proven research track record witnessed by peer reviewed publications and collaborations and relevant teaching experience.
They will be expected to contribute to the Information Engineering research group obtaining external funding to enable development of excellent independent research. They will be expected to contribute to the teaching of undergraduate courses in the Department of Engineering Science, which may include lectures, tutorials and practical classes, and the supervision of undergraduate design and project work, and pastoral care of graduate students in College.

Further particulars, containing full details of the application procedure and duties, are to be found at http://www.eng.ox.ac.uk/about-us/jobs/df12kel The closing date is noon, 20 July 2012.

Prof. Paul Newman
BP Professor of Information Engineering
Dept Engineering Science
University of Oxford

CEP – Conversational Engagement Prediction – a challenge

We have collected a large dataset in group video-mediated communication
context and now we run the following challenge as part of the upcoming
ACM ICMI conference challenges:

http://d-meta.inrialpes.fr/tasks/cep-conversational-engagement-prediction/

I would be happy to provide more information and I would also
appreciate if you could distribute this information to people who are
interested in conversational engagement and multimodal signal analysis.

best,

–Roman

—–

D-META Grand Challenge
http://d-meta.inrialpes.fr

at the International Conference of Multimodal Interaction (ICMI)
Santa Monica, October 2012.

The D-META Grand Challenge (Datasets for Multimodal Evaluation of Tasks
and Annotations) proposes to set up the basis for comparison, analysis,
and further improvement of multimodal data annotations and multimodal
interactive systems. Held by two coupled pillars, method benchmarking
and annotation evaluation, the D-META challenge envisions a starting
point for transparent and publicly available application and annotation
evaluation on multimodal data sets. We expect papers covering areas such
as: (i) applications of an algorithm to a data set(s) to solve precise
tasks, (ii) benchmark of several algorithms using the same data set(s),
(iii) extensions of the annotation scheme with new relevant features,
(iv) applications of the data to an automatic system, (v) discussions on
ecologically valid data sets and (vi) position papers of how to organize
the next challenge. Papers may target one of the following tasks
(http://http://d-meta.inrialpes.fr/tasks/) :

AVRGR Recognize gestures addressed to the robot by means of the
vision and the audio.
AVSR Detect, localize and track multiple speakers using
audio-visual information.
CEP Estimate the level of engagement in a video-mediated communication.
AVCGR Recognize conversational gestures in first encounter dialogues.
AVFGR Recognize feedback gestures in first encounter dialogues.

Please check the web site for more information:
http://d-meta.inrialpes.fr and keep in mind the important dates:

31-Jul-2012 Paper deadline
24-Aug-2012 Author notification
14-Sep-2012 Camera-ready
Oct-2012 Work presented at D-META’12

Hope you all take the time to participate and/or disseminate this
information.

The D-META Grand Challenge Team.

PhD Scholarships – IMT Institute for Advanced Studies

IMT Institute for Advanced Studies Lucca (www.imtlucca.it) is accepting applications, from extremely motivated students oriented towards dynamic and highly applicative research opportunities, for fully-funded positions in its
2013 Doctoral Research Program.

The Track in Computer, Decision, and Systems Science (CDSS) aims to equip researchers and professionals with a wide knowledge of the theoretical foundations of computer science, informatics and system analysis that are applicable to a large variety of real-life problems of industrial, managerial, economic, and societal interest. Such elements include control systems, management science, optimal decision making and numerical optimization, image analysis and pattern recognition. The objective of the program is to provide Ph.D. candidates with the necessary scientific competence to master the theoretical aspects of the discipline, to propose original research ideas, and to develop numerical algorithms, managerial solutions and software tools for applying the new concepts to practical applications.

The Track in Computer, Decision and Systems Science is organized into four
curricula:

Computer Science (CS)
The curriculum in Computer Science (CS) focuses on key aspects of informatics, such as open-endedness, autonomy, security, concurrency, cost-effectiveness, quality of services, and dependability. The main goal is to study models, algorithms, and verification methods for modern distributed systems. The doctoral students enrolled in this curriculum will acquire extensive knowledge of the fundamentals and applications of architectures and languages for such distributed systems, including global and grid cloud computing systems, web systems and services, embedded systems, web data mining, and mobile systems. They will also learn professional skills for the application of computer technologies to wide area networks.

Control Systems (SYS)
The curriculum in Control Systems (SYS) is oriented towards model-based control of dynamical systems and decision-making algorithms, including embedded optimization algorithms for control and management of stochastic, networked, and large-scale dynamical systems. Motivated by the pervasive nature of data information systems and by the availability of powerful (and possibly distributed) computational resources, the main goal is to devise complex decision-making strategies that make systems react with a certain degree of autonomy and in an intelligent way to changes in their operating environment. Research skills in model-based control and optimization of dynamical systems taught enable students to conceive novel theories and algorithms. Students also learn professional skills for designing, simulating, and deploying control systems in a variety of application areas, such as smart grids and energy markets, finance, automotive and aerospace systems, water network management, industrial processes and many others.

Image Analysis (IA)
The curriculum in Image Analysis (IA) focuses on the analysis of large-scale multimodality imaging data for life sciences. Motivated by the explosion in biomedical imaging data, the goal is to develop high-throughput and high-precision strategies to analyze intelligently these vast data sets to prove clinically-driven hypothesis and unearth unseen patterns. Such vast datasets arise from studies of various organs (heart, brain and vasculature) and organisms (humans, other model organisms such small or large animals, and plants), using multiple modalities (MRI, PET, and optical at various scales), which span multiple dimensions (2D, 3D, monotone and multispectral), and are dynamic and repeated. This scenario is particularly prevalent now, where this type of analysis is needed to speed up phenotyping studies that accompany genotype-driven experiments.

Management Science (MS)
The curriculum in Management Science (MS) is oriented towards managerial decision making in complex organizations based on a quantitative approach to finance, marketing, information systems, operations, organizational behavior, innovation and industrial dynamics. Track participants are expected to acquire a solid grasp of underlying principles of information theory, decision sciences, statistics and numerical methods, along with their organizational and economic implications. Students and faculty address research questions raised by the emerging digital economy, the transformation of organizations and markets, and opportunities for new business models. MS is inherently multi-disciplinary. Study in this area utilizes faculty with backgrounds in economics, management science, computer science, decision sciences and complex system analysis. Although the program is primarily designed to prepare candidates for leading academic positions in top business and industrial engineering schools, a number of our graduates also assume high-level consulting or other industry positions.

Each student is invited to construct a personal study plan with Advisor, drawing from entire range of course offerings, to best suit his or her background and research interests.

Please visit the call website
(http://www.imtlucca.it/phd/call_for_applications/index.php) for more details regarding program content, the numerous benefits that students enjoy (including scholarships and room and board), and for the online form.

Please apply online ONLY by September 26th 2012.

IMT is also accepting applications in the fields of:

• Economics
• Management and Development of Cultural Heritage
• Political History

Those interested will be able to hear a real-time presentation of the program on an interactive webinar scheduled for June 28th 2012 (after this date a recording of the same will be available for viewing). To sign up, go to www.brightrecruits.com/webinars.

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