CVPR workshop on gesture recognition

CVPR Workshop on Gesture Recognition
and launching of a benchmark program
June 20, 2011
Colorado Springs, USA
http://clopinet.com/isabelle/Projects/CVPR2011/

We are organizing a workshop of gesture and sign language recognition from video data and still images. Gestures can originate from any body motion or state but commonly originate from the face or hand. Much recent research has focused on emotion recognition from face and hand gestures, with applications in gaming, marketing, and computer interfaces. Many approaches have been made using cameras and computer vision algorithms to interpret sign language for the deaf. However, the identification and recognition of postures and human behaviors is also the subject of gesture recognition techniques and has gained importance in applications such as video surveillance. This workshop aims at gathering researchers from different application domains working on gesture recognition to share algorithms and techniques.

Papers due: April 2, 2011

Invited speakers:
Aleix Martinez, Ohio State University, USA.
Greg Mori, Simon Fraser University, Canada.
Richard Bowden, Univ. Surrey, UK.
Graham Taylor, NYU, New-York.
David Forsyth, University of Illinois at Urbana-Champaign.
Sudeep Sarkar, University of South Florida.
Dimitri Metaxas, Rutgers University, New Jersey.
Maja Pantic, Imperial College, London.
Christian Vogler, Institute for Language and Speech Processing, Athens, Greece.
Takeo Kanade, Carnegie Mellon University.

Organizing committee:
Isabelle Guyon, Clopinet, Berkeley, California
Vassilis Athitsos, University of Texas at Arlington
Jitendra Malik, UC Berkeley, California
Ivan Laptev, INRIA, France

Manchester Centre for Doctoral Training

Please see below details of our new Centre for Doctoral Training – with Manchester’s strong
community in machine learning, computer vision, and pattern recognition, we will particularly
welcome applicants from the PASCAL network.

Centre for Doctoral Training in Computer Science – Join us!
===========================================================

Students considering PhD study are invited to apply to the new Manchester Centre for
Doctoral Training in Computer Science, the first of its kind in the UK.

http://cdt.cs.manchester.ac.uk/

The centre, funded by a £2.2 million grant from the UK Engineering and Physical Sciences
Research Council (EPSRC), will admit at least 75 students over the next five years.

Our mission is to train the computer scientists of the future, thorough offering a radically
different approach to the doctoral training process. Students admitted to the centre will be
given the chance to become “the complete researcher”, supported by funded studentships the
cover the full duration of the 4 year programme.

Programme Details
=================
Students will receive training in all aspects of the research process:
creativity and innovation, research problem solving in collaboration with industrial users and
carrying out research with real world impact.
At the same time students will complete significant research in collaboration with world-
leading academic staff.

The programme consists of an initial ‘foundation period’ of six months of taught
components, followed by a 3.5 year period of focused PhD level research, carried out under
the supervision of a PhD supervisor or team of supervisors. For further information about the
programme, please see details here:

http://cdt.cs.manchester.ac.uk/programme/

Studentships
============
Studentships pay home tuition fees and a full stipend for 4 years. We have over 15 fully-
funded studentships available for UK and EU students.
For further information regarding funding, please see our funding page:

http://cdt.cs.manchester.ac.uk/fees/funding/

Who should apply?
=================
We welcome applications from students with a First or Upper Second Class UK Honours
degree or equivalent in a relevant science or engineering discipline. Further information can
be obtained by e-mail:
cdt(at)cs.man.ac.uk
or telephone:
+44 (0)161 275 0699

Or by visiting our website: http://cdt.cs.manchester.ac.uk/

CDT Background
==============
The University won the grant despite strong competition from other leading computer science
departments across the UK. The awarding panel felt strongly that the proposal represented an
excellent opportunity to make a real impact to doctoral training in the UK.

Professor Steve Furber, director of the new centre, said: “We are delighted to have been
chosen by EPSRC for this flagship Centre for Doctoral Training in Computer Science, and
look forward to rising to the challenge of using this opportunity to transform computing
PhDs in the UK.”

ICML workshop on Unsupervised and Transfer Learning

ICML workshop on Unsupervised and Transfer Learning
July 2, 2011, Bellevue, Washington state, USA

and UTL Challenge (phase 2: transfer learning — $3000 in prizes)
http://clopinet.com/isabelle/Projects/ICML2011/

If you are working on transfer learning or kernel learning, you may want to consider entering the challenge we are currently running.
The goal is to demonstrate that you can learn data representations or kernels, which can be re-used across similar tasks.

We have an accepted workshop at ICML [entering the challenge is not a requisite to submit a paper to the workshop and vice versa].

– Challenge deadline: April 15
– Paper deadline: April 29
– Challenge website: http://clopinet.com/ul
– YouTube video (only 15 min) if you want to learn about transfer learning: http://www.youtube.com/watch?v=9ChVn3xVNDI
– The proceedings will be published in JMLR W&CP and as a book in the CiML series of Microtome publishing.

Riemann manifold Langevin and Hamiltonian Monte Carlo methods – now published with discussion

Riemann manifold Langevin and Hamiltonian Monte Carlo methods
Mark Girolami, Ben Calderhead

Journal of the Royal Statistical Society: Series B (Statistical Methodology)
Volume 73, Issue 2, pages 123–214, March 2011

The above paper plus discussion and rejoinder has now been published in the latest edition of the Journal of the Royal Statistical Society, Series-B. There were over 60 contributions to the discussion which I am informed is something of a record for RSS read papers. The paper + discussion + rejoinder can be downloaded from the Wiley website at

http://onlinelibrary.wiley.com/doi/10.1111/rssb.2011.73.issue-2/issuetoc

The website http://www.ucl.ac.uk/statistics/research/rmhmc will be updated as further related publications and codes become available.

Best Regards
Mark Girolami

The 2011 Lisbon Machine Learning School (LxMLS) – call for participation

The 2011 Lisbon Machine Learning School (LxMLS)

Call for participation.

Lisbon, 20-25 July, 2011.

Web: http://lxmls.it.pt/

The target audience includes researchers and graduate
students in the fields of natural language processing
(NLP) and computational linguistics, computer scientists
with interests in statistics and machine learning (ML),
and practitioners desiring a more in-depth understanding
of these subjects.

LxMLS will not assume deep previous knowledge of ML or
NLP; recommended reading will be provided in advance.
The school will include a strong practical component.
Both basic and advanced topics will be covered. All the
instructors are leading researchers in ML and/or NLP.

Application deadline: March 31, 2011.

Research Associate (Training Fellowship – Machine Learning) Opening at Gatsby Unit, UCL

Research Associate (Training Fellowship – Machine Learning) – Ref:1179724

Gatsby Computational Neuroscience Unit, UCL

Grade: 7
Hours: Full Time
Salary (inclusive of London allowance): £34,604 –£38,594 per annum
Closing Date: 8 Apr 2011
Latest time for the submission of applications: 12 noon.
Interview date: 6th May, 2011

Duties and Responsibilities

The Gatsby Computational Neuroscience Unit invites applications for a training fellowship in machine learning and related areas. The Unit is especially keen to recruit researchers with expertise in probabilistic and Bayesian modelling, time series modelling, reinforcement learning and control.

The Unit is a world-class centre for theoretical neuroscience and machine learning. The Unit has significant interests across a range of areas in machine learning, including unsupervised learning, reinforcement learning, Bayesian modeling, statistical theory, nonparametric methods, kernel methods, optimization, and applications to neuroscience, linguistics, vision and bioinformatics. Machine learning research at the Gatsby Unit is led by Yee Whye Teh and Arthur Gretton.

For further details of our research please see: http://www.gatsby.ucl.ac.uk/research

The Unit provides a unique environment in which a critical mass of researchers interact closely with each other and with other world-class research groups in related departments at UCL. A cross-faculty Centre for Computational Statistics and Machine Learning opened at UCL in 2006, currently directed by Mark Girolami and spanning the departments of Computer Science, Statistical Science and the Gatsby Unit. The Unit’s visitor and seminar programmes enable staff and students to engage with leading researchers from across the world.

Training fellowships that are funded by the Gatsby Charitable Foundation are part of a continuing program of training postdoctoral researchers in the discipline. The position is available for an initial period of between one and two years. Due to the joint funding arrangement of this training fellowship, the post may be funded up to a maximum of four years subject to the requirements of the project.

Key Requirements

Candidates must have a PhD in a relevant subject area by the agreed start date of the position, and possess strong analytical and computational background with demonstrable interest and expertise in machine learning.

Further Details: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041178&ownertype=fair&jcode=1179724

Click on ‘Further Information’ at bottom of webpage for a full Job Description and Person Specification.
To apply for the vacancy, please click on the ‘Apply Now’ button on the webpage given above.

If you have any enquiries regarding the vacancy please contact ywteh(at)gatsby.ucl.ac.uk. For queries relating to the application process, please contact asstadmin(at)gatsby.ucl.ac.uk

This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff.

UCL Taking Action for Equality

UCL Terms and Conditions related to this job: http://www.ucl.ac.uk/hr/salary_scales/Support_Research_tcs.php
Employee benefits that we offer: http://www.ucl.ac.uk/hr/benefits/employee_benefits.php
and further information about UCL: http://www.ucl.ac.uk/hr/docs/download_forms/recruitment_selection_N.doc

Further particulars: https://filesv7.wcn.co.uk/admin/fairs/apptrack/download.cgi?SID=b3duZXI9NTA0MTE3OCZvd25lcnR5cGU9ZmFpciZkb2NfdHlwZT12YWMmZG9jX2lkPTYxMjkzJnZlcmlmeT1kOTYzMGI4MGIxOGRlZDE1MDdmYzZhZmY1MmI1MGZjOSZ1cmxfa2V5PTI3MjQyNzI2M2YyMzIwMmIyYjIwMjEyYTIwMjMyYTNmNzE3MDc0NzMyMjJiNzAyNzJhMjUyMzJiNzcyNTc0MjEyMzI0NzEyMDc3NzQ3NDc3NzMyMTcxMjEyYjJhMjQyMTI3MjY3NjI1MjUyYTcwNzExMg==

Ghana Moves Up In Computer Application Systems

Ghana has joined the ranks of privileged few countries that apply artificial intelligence (AI), a branch of computer science that aims to create the intelligence in machines and computers to mimic human behaviour.

Artificial Intelligence (AI) is a computer application system by which machines are empowered to mimic the actions and behaviour of human beings. This enables machines to perform tasks more efficiently and reliably.

AI applications can be used to determine patterns in huge volumes of data obtained from educational institutions, hospitals, banks, insurance companies and are capable of predicting trends that are useful for planning and forecasting.

The field was founded on the assumption that a central property of humans— intelligence—can be so precisely described that it can be simulated by a machine.

The Ghana-India Kofi Annan Centre of Excellence in ICT (AITI-KACE), in partnership with the PASCAL Network of Excellence and Stefan Josef Institute in Europe, has started an eight-day boot camp on artificial intelligence (AI) for researchers and lecturers from some of leading universities in Ghana and Nigeria.

The boot camp is to prepare the grounds for the establishment of an AI laboratory for Ghana to support academic and research work in this area.

As part of the partnership with AITI-KACE, the European institutes have presented an AI research software, CYC, to the centre of excellence to help researchers and lecturers to deepen their knowledge in AI, which helps humans to accomplish tasks more efficiently as the machines are trained to mimic the behaviour of humans with a high level of accuracy and precision.

One of the Course Facilitators, Dr Micheal J. Witbrock of the European Cycorp Incorporated, told the Daily Graphic that AI could be applied in many areas of the Ghanaian society and economy to solve challenges, no matter how difficult and novel.

He explained that with AI, the programmes, software and the machines were fed with so much facts about a subject, with the machines empowered to make inferences and conclusions with precision which could help solve problems that humans had hitherto found difficult.

For example, in the fight against malaria, an AI application could help medical practitioners diagnose, with ease and precision, the type and intensity of the ailment and make super accurate prescriptions, giving answers to how the prescriptions could be obtained.

Interestingly, the software, CYC, could go further to help translate the work into different natural languages (languages spoken in the local area), breaking the literacy and communications barriers to any form of research or medical treatment.

Areas of applied AI includes robotics; perceptive systems, which has to do with human sensing; and expert systems, a complete attempt to make machines replace human characteristics.

Currently, AI technology does a lot of things, including the recognition of voices and performs real time translation in other languages, with the expectation that in five years computers would have been developed that could answer any type of question fed into it.

Besides its use in the medical field, AI applications can be helpful in the fight against corruption as it could be deployed to track the quality of expenditure, monitor their transmission, check fraud and ensure the efficient use of resources.

Dr Witbrock said the boot camp was to stimulate the interest in AI in Ghana as a hub to West Africa, as well as get contributions from Ghanaian course participants.

The Director of the AITI-KACE, Ms Dorothy K. Gordon, said AI would help people enrich their work, while creating avenues for retraining people to do other work.

She said the boot camp was to enable Ghana to benefit from a transfer of knowledge in the area from Europe, adding that a foundation would be established to support the development of AI in Ghana.

While thanking the partners for the software licence made available for research, Ms Gordon said the PASCAL Network had also presented cameras, books and other logistics to facilitate the deepening of AI in Ghana.

The boot camp is to transfer and share technical knowledge on Artificial learning to participants from the Kwame Nkrumah University of Science and Technology (KNUST), the University of Ghana, the Ghana Institute of Management and Public Administration (GIMPA), Ashesi University and Regent University.

Full article available at http://www.modernghana.com/news/317659/1/ghana-moves-up-in-computer-application-systems.html

PhD position at University of Nantes: Grammatical inference of probabilistic context-free grammars

This position is offered at the University of Nantes in the LINA research lab, in the natural language processing group and is funded by the region “Pays de Loire”.

Grammatical inference is about learning grammars or automata for a language, given partial information, typically strings, about the language. If the situation for finite state machines is fairly well understood (which doesn’t mean solved!) the situation for context-free languages and grammars is still far from clear. Some algorithms exist, but there is room for improvement, in a problem which is important for many applications, of which natural language processing. Probabilistic context-free grammars are context-free grammars in which each rule has a probability of being used: these grammars allow to define interesting distributions over sets of strings. The goal of this PhD is to reconsider different strategies in order to study the learnability of probabilistic context-free grammars, to propose new algorithms and to experiment these on NLP applications.

Applications are invited for a fully funded studentship on the topic stated above.

Qualifications required:
– Master’s in Computer Science or a related field.
– Good mathematical understanding.
– High motivation for research.
– Capability of working in an autonomous way.
– Good programming skills.
– Good communication skills in English, both in written and oral form.
– Experience and detailed knowledge of machine learning, algorithmics, formal language theory and/or statistics will be an asset.
Applicants should submit a complete CV and recommendation letters to cdlhuniv-nantes fr.

Applications are open until the end of the Spring 2011.

The PhD will start (unless otherwise negociated) in September 2011, and the student will be funded during 3 years.

Salary: Standard French PhD scholarship (20K€ p.a.). This salary is compatible with other schemes allowing the student to be able to teach (for example). For more information about these questions, please contact Colin de la Higuera.
http://pagesperso.lina.univ-nantes.fr/~cdlh/

Assistant Professor Positions in Learning / Optimization / Medical / Vision – Ecole Centrale de Paris / INRIA

École Centrale Paris,
http://www.ecp.fr / http://www.inria.fr,
INRIA Saclay, IDF,
http://www.inria.fr/centre-de-recherche-inria/saclay-ile-de-france

Description :
The Department of Applied Mathematics at Ecole Centrale Paris and the
INRIA Saclay, Ile-de-France Research Center invite applications for
several research faculty positions at the level of assistant professor.
These are five-year fixed term appointments with possible renewal. We
give higher priority to the overall originality and promise of the
candidate’s work.

Mission :
We are seeking applicants in the areas of machine learning, optimization
(with emphasis eventually on discrete methods). We are also interested
in applicants doing research at the Frontiers of Computer Science,
Applied Mathematics and Bioengineering with emphasis on computational
vision, biomedical imaging and human-computer interaction.

Profile :
Applicants must have completed (or be completing) a Ph.D. in the above
mentioned fields, must have demonstrated the ability to pursue a
cutting-edge program of research, and expected to (minimally) contribute
to graduate (and undergraduate) teaching in their Respective research areas.

How to apply:
Applications should include a curriculum vita, brief statements of
research and teaching interests (three pages), and the names of at least
three references. Candidates are requested to ask References to send
their letters directly to the search committee.

Applications and letters should be sent to: Search Committee Chairs, via
electronic mail to:
o Prof. Nikos Paragios, nikos.paragios@ecp.fr
o Prof. Lionel Gabet, lionel.gabet@ecp.fr

École Centrale Paris is one of the top three engineering schools in
France, part of the elite of “Grande Écoles” offering access to
excellent quality graduate and under-graduate students while INRIA is
one of the most reputable research institutes world wide. These
positions offer full health, unemployment and retirement benefits and
highly competitive salaries.

The review of applications will begin on April 1, 2011, and applicants
are strongly encouraged to submit applications by that date; however,
applications will continue to be accepted at least until May 1, 2011.

ECML PKDD 2011 Second Call for Papers

ECML PKDD 2011 – The European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases

September 5-9, 2011
Athens, Greece
http://www.ecmlpkdd2011.org/

Key Dates
Abstract submission deadline: April 5, 2011
Paper Submission deadline: April 12, 2011
Paper Acceptance Notification: June 3, 2011
Paper Camera Ready: June 12, 2011

Call For Papers
The European Conference on “Machine Learning” and “Principles and Practice
of Knowledge Discovery in Databases” provides an international forum for
the discussion of the latest high quality research results in all areas
related to machine learning and knowledge discovery in databases and
other innovative application domains.

We invite submissions on all aspects of machine learning,
knowledge discovery and data mining. We especially encourage submissions of
papers that describe the application of machine learning and data mining methods
to real-world problems, and highlight new research challenges in new domains such as
the web, medicine, biology, neuroscience, engineering, government fields.
Submissions that demonstrate both theoretical and empirical rigor are also highly encouraged.

Proceedings and Special Journal Issues
The conference proceedings will be published by Springer Verlag (“Lecture
Notes in Artificial Intelligence Series”).
A selection of papers will be published in two post-conference special
issues of the Springer Verlag journals “Data Mining and Knowledge Discovery”
and “Machine Learning”.

Submissions
All aspects of the submission and notification process will be handled
online
via the Microsoft CMT.

The papers must be written in English and formatted according to
the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines.
Authors instructions and style files can be downloaded at:
http://www.springer.de/comp/lncs/authors.html

The maximum length of papers is 16 pages in this format.

Papers submitted should report original work; ECML PKDD 2011 will
not accept any paper which, at the time of submission, is under
review or has already been accepted for publication in a journal
or another conference. Authors are also expected not to submit
their papers elsewhere during the review period.

Papers submitted to ECML PKDD 2011 will normally be reviewed by
minimum of two referees. The review process will be double blind.
Student submissions should be clearly indicated on the submission form.

Conference Organization
General co-Chairs
Prof. Aris Likas (Univ. of Ioannina, Greece)
Prof. Yannis Theodoridis (Univ. of Piraeus, Greece)

Program Commitee chairs
Prof. Dimitris Gunopulos (Univ. of Athens, Greece)
Dr. Thomas Hofmann (Google Research)
Prof. Donato Malerba (Univ. of Bari, Italy)
Prof. Michalis Vazirgiannis (Athens Univ. of Economics and Business, Greece)

Venue
ECML PKDD 2011 will take place in Athens, Greece. Athens is the capital of
Greece, standing at a strategic point in southeastern Europe,
with unique historical and cultural assets and a location of exceptional
natural beauty, privileged with a perfect weather climate.

Conference Web Page & Social Networking
Please visit regularly the conference web page to get the latest updates in
the conference:
http://www.ecmlpkdd2011.org

You may want to join the relevant FACEBOOK group:
http://www.facebook.com/pages/ECML-PKDD-2011/111315008934900
or follow us on TWITTER at: http://www.twitter.com/ECML_PKDD_2011