Post-doc position at INRIA (LEAR team)

The LEAR team at INRIA Grenoble is looking for a qualified post-doctoral researcher with a specialization in Computer Vision and Machine Learning, on the topic of discovering relationships between actions and objects.

The position is offered at the “Rhone-Alpes” Research Unit of INRIA, located near Grenoble and Lyon. The Unit includes more than 600 people, within 26 research teams and 10 support services.

Starting date: Summer 2009

Deadline for applications: June 2009.

Monthly salary after taxes : 1 983 € (medical insurance included)

Contact: Remi.Ronfard (at) inrialpes.fr

Activities

Recently, a number of image ranking approaches were proposed that build upon visual words similarity networks (i.e. [3,4]). These methods explore relationships between object categories by analyzing similarities of the extracted visual features. In the case of video actions, the relationships are more complex as similarities can be observed in the spaces of image features, motion features, and also in the joint space of image and motion features. An approach to discovering relationships in such networks would allow for recognition of objects, motions, and human-object interactions. The initial investigation can be performed along the lines in [3,4].

In order to achieve the above goal, a good feature extraction method has to be developed. Existing spatio-temporal features describe information of a video subvolume of a simple shape. Intuitively, the procedure that discovers the shapes of such subregions should be guided by some general measure of the subregion descriptiveness. Unfortunately, straightforward extensions of the common 2D subregion extraction methods [1] may not be appropriate. Additionally, approaches to obtaining good descriptors of the extracted subregions should be investigated., with special care taken to obtain good view and time-invariant spatio-temporal descriptors.

In order to investigate the relationships between actions and objects, the problem of analyzing human-object interactions should be addressed. It would be of significant practical benefit to have a method for recognizing interactions from an egocentric

camera. Ideally, the approach would discover atomic interactions from sequences of long-term activities. Some of the possible approaches to implement the idea would be to consider the interaction models [2].

Skills and Profile

* PhD degree (preferably in Computer Vision or Machine Learning)

* 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 action recognition, video retrieval or object recognition is a plus

REFERENCES

[1] A. Oikonomopoulos, I. Patras, and M. Pantic, Human action recognition with spatiotemporal salient points, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, vol. 36, no. 3, pp. 710-719, 2006.

[2] Hedvig Kjellstrasom, Javier Romero, David Martinez Mercado, and Danica Kragic, Simultaneous visual recognition of manipulation actions and manipulated objects, in ECCV (2), 2008, pp. 336-349.

[3] Gunhee Kim, C. Faloutsos, and M. Hebert,Unsupervised modeling of object categories using link analysis techniques, in CVPR, 2008,pp. 1-8.

[4] Yushi Jing and Shumeet Baluja, Visualrank: Applying pagerank to large-scale image search, TPAMI, vol. 30, no. 11, pp. 1877-1890, 2008.

Research Scientist position – XEROX Research Centre Europe – Grenoble, France

Text and Visual Pattern Analysis

XEROX Research Centre Europe’s Text and Visual Pattern Analysis Area (TVPA) is an expanding team, which specializes in text and visual content understanding. Our mission is the delivery of Xerox’s innovative solutions that make everyday interaction with visual and textual content simple and effective. Our research is the result of combining skills mainly in machine learning, pattern recognition and image analysis. In particular we focus on text and image categorization, image enhancement, quality assessment and document imaging.

Your Job: Research Scientist

As a research scientist in TVPA you will be asked to generate and follow up on new ideas, on build strong competencies and intellectual property in Computer Vision and Pattern Analysis. In particular, you will be pursuing activities around our new research agenda on Applied Visual Aesthetics.

Moreover, you will collaborate in a small, agile team that leads the development of the OMNIA Project. OMNIA is a three year project funded by French Government aiming at developing innovative strategies for multimodal asset retrieval based on three main axes: content, emotion and visual aesthetics.

Research Topics:

* Design of aesthetic measures (light/colour harmony/composition analysis, aesthetic ontology design, user preference regression etc.)

* Image mood analysis (development of features capturing emotional content of visual information, design of classifiers for automatic labeling of assets)

* Assisted content creation and Image personalization (asset selection, features transfer, colour harmonization, etc.)

Responsibilities:

1. Inventing, implementing and evaluating novel imaging software.

2. Studying the state of the art, disseminate results on international conferences and journal papers, fulfill project deliverables.

3. Collaborating with other project partners in order to integrate the research results in a common environment/platform (sharing components, algorithms and methods).

Requirements

– PhD in Computer Science with a strong history of systems building and publishing

-Deep and substantial background on Pattern Recognition/Computer Vision and Image Processing

-Strong English-language written and oral communications skills

Expected start date: Mid June 2009

Type of contract: Temporary position – 18 months

To apply: Please send your CV and cover letter to: luca.marchesotti (at) xrce.xerox.com, xrce-candidates (at) xrce.xerox.com

PhD Position in Machine Translation and Speech Understanding (starting 09/09)

The PORT-MEDIA (ANR CONTINT 2008-2011) is a cooperative project sponsored by the French National Research Agency, between the University of Avignon, the University of Grenoble, the University of Le Mans, CNRS at Nancy and ELRA (European Language Resources Association). PORT-MEDIA will address the multi-domain and multi-lingual robustness and portability of spoken language understanding systems. More specifically, the overall objectives of the project can be summarized as:
– robustness: integration/coupling of the automatic speech recognition component in the spoken language understanding process.
– portability across domains and languages: evaluation of the genericity and adaptability of the approaches implemented in the understanding systems, and development of new techniques inspired by machine translation approaches.
– representation: evaluation of new rich structures for high-level semantic knowledge representation.

The PhD thesis will focus on the multilingual portability of speech understanding systems. For example, the candidate will investigate techniques to fast adapt an understanding system from one language to another and creating low-cost resources with (semi) automatic methods, for instance by using automatic alignment techniques and lightly supervised translations. The main contribution will be to fill the gap between the techniques currently used in the statistical machine
translation and spoken language understanding fields.

The thesis will be co-supervised by Fabrice Lefèvre, Assistant Professor at LIA (University of Avignon) and Laurent Besacier, Assistant Professor at LIG (University of Grenoble). The candidate will spend 18 months at LIG then 18 months at LIA.

The salary of a PhD position is roughly 1,300€ net per month. Applicants should hold a strong university degree entitling them to start a doctorate (Masters/diploma or equivalent) in a relevant discipline (Computer Science, Human Language Technology, Machine Learning, etc). The applicants should be fluent in English. Competence in French is optional, though applicants will be encouraged to acquire this skill during training. All applicants should have very good programming skills.

For further information, please contact Fabrice Lefèvre (Fabrice.Lefevre at univ-avignon.fr) AND Laurent Besacier (Laurent.Besacier at imag.fr).

MCBR-CDS09: CALL FOR PAPERS

CALL FOR PAPERS
MCBR-CDS 2009: Medical Content-based Retrieval for Clinical Decision Support
September 20th, 2009
London, UK
http://www.almaden.ibm.com/cs/projects/aalim/multimodal-decision.html

** Paper Submisions Due May 22th, 2008 **

——————-
Call for Papers
——————-

Diagnostic decision making (using images and other clinical data) is still very much an art for many physicians in their practices today due to a lack of quantitative tools and measurements. Traditionally, decision making has involved using evidence provided by the patient’s data coupled with a physician’s a priori experience of a limited number of similar cases. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now becoming available. These datasets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structured clinical data). Analyzing these multimodal sources for disease-specific information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disease-specific information in modalities to find supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past five years to include large medical image collections for testing various algorithms for medical image retrieval. This has made comparisons of several techniques for visual, textual, and mixed medical information retrieval as well as for visual classification of medical data possible based on the same data and tasks.
The goal of this workshop is to bring together researchers in medical imaging, medical image retrieval, data mining, text retrieval, and machine learning/AI communities to discuss new techniques of multimodal mining/retrieval and their use in clinical decision support. We are looking for original, high-quality submissions that address innovative research and development in the analysis, search and retrieval of multimodal medical data for use in clinical decision support. Further, to encourage a larger group of image analysis researchers to profit from the databases and evaluations created in the context of ImageCLEF, we will provide access to the medical databases and tasks of ImageCLEF 2009 which has obtained rights from RSNA to use over 70,000 images of the journals Radiology and Radiographics.

Topics for the workshop include but are not limited to:
–Mining of multimodal medical data (X-ray, MRI, CT, echo videos, time series data)
–Machine learning of disease correlations from mining multimodal data
–Algorithms for indexing and retrieval of data from multimodal medical databases
–Disease model-building and clinical decision support systems based on multimodal analysis
–Practical applications of clinical decision support using multimodal data retrieval or analysis
–Algorithms for medical image retrieval

————————–
Paper Submission
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Prospective authors are invited to submit papers of not more than
eight(8) pages including results, figures and references. Please use
the MICCAI author kit to format the papers.

————————
Important Dates
————————
Paper submission deadline: May 22nd, 2009

Notification of acceptance: June 28th, 2009

Camera ready copy : July 20th, 2009

Workshop date: September 20th 2009

Extended CfP: NUMML 2009 (ICML 2009 Workshop on Numerical Mathematics in Machine, Learning)

Extended: CALL FOR CONTRIBUTIONS

International Conference on Machine Learning (ICML)

Workshop on Numerical Mathematics in Machine Learning

June 18, 2009. Montreal, Canada

http://numml.kyb.tuebingen.mpg.de

*Deadline for abstract submissions: 8th May, 2009 (EXTENDED Date)*

Most machine learning (ML) algorithms rely fundamentally on concepts of numerical mathematics. Standard reductions to black-box computational primitives do not usually meet real-world demands and have to be modified at all levels. The increasing complexity of ML problems requires layered approaches, where algorithms are components rather than stand-alone tools fitted individually with much human effort. In this modern context, predictable run-time and numerical stability behavior of algorithms become fundamental. Unfortunately, these aspects are widely ignored today by ML researchers, which limits the applicability of ML algorithms to complex problems.

Our workshop aims to address these shortcomings, by trying to distill a compromise between inadequate black-box reductions and highly involved complete numerical analyses. We will invite speakers with interest in *both* numerical methodology *and* real problems in applications close to machine learning. While numerical software packages of ML interest will be pointed out,
our focus will rather be on how to best bridge the gaps between ML requirements
and these computational libraries. A subordinate goal will be to address the role of parallel numerical computation in ML.

Examples of machine learning founded on numerical methods include low level computer vision and image processing, non-Gaussian approximate inference, Gaussian filtering / smoothing, state space models, approximations to kernel methods, and many more.

The workshop will comprise a panel discussion, in which the invited speakers are urged to address the problems stated above, and offer individual views and suggestions for improvement. We highly recommend active or passive attendance at this event. Potential participants are encouraged to contact the organizers beforehand, concerning points they feel should be addressed in this event.

Invited Speakers:

Inderjit Dhillon University of Texas, Austin
Michael Mahoney Stanford University
Jacek Gondzio Edinburgh University, UK
Dmitry Malioutov MIT

Topics:

Potential short talks / posters should aim to address:

– Raising awareness about the increasing importance of stability and predictable run-time behaviour of numerical machine learning algorithms and primitives
– Stability and predictable behaviour as a criterion for making algorithm choices in machine learning
– Lessons learned (and not learned) in machine learning about numerical mathematics. Ideas for improvement
– Novel developments in numerical mathematics, with potential impact on machine learning problems

Contributions will be considered only if a clear effort is made to analyze problems that arise, and if choices of algorithms, preconditioning, etc. are clearly motivated. For reasons stated in “Motivation”, submissions that apply numerical methods in a black box fashion, or that treat numerical techniques without motivating the use for machine learning, cannot be considered. The usual “smoothing over problems” conference paper style is discouraged, and naming and analyzing problems is strongly encouraged.

Potential Subtopics (submissions are not limited to these):

A- Solving large linear systems
-Arise in the linear model/Gaussian MRF (mean computations), nonlinear optimization methods (Newton-Raphson, IRLS, …)
-Preconditioning, use of model structure.
-Our main interest is on semi-generic ideas that can be applied to a range of machine learning real-world situations
B- Novel numerical software developments relevant to ML
-Parallel implementations of LAPACK, BLAS
-Sparse matrix packages
C- Approximate eigensolvers
-Arise in the linear model (covariance estimation), spectral clustering and graph Laplacian methods, PCA
-Lanczos algorithm and specialized variants
-Preconditioning
D- Exploiting matrix/model structure, fast matrix-vector multiplication
-Matrix decompositions/approximations
-Multi-pole methods
-Signal-processing primitives (e.g., variants of FFT)
F- Parallel numerical computation for ML
G- Other numerical mathematics (ODEs, PDEs, Quadrature, etc.) focusing on machine learning

Submission Instructions:

We invite submissions of extended abstracts, from 2 to 4 pages in length (using the ICML 2009 style file). Criteria for content are given in “Topics”. Submissions should be sent to suvadmin (at) googlemail.com

Accepted contributions will be allocated short talks or posters. There will be a poster session with ample time for discussion. Short talk contributions are encouraged to put up posters as well, to better address specific questions.

Important Dates:

Submissions due: May 8, 2009
Author notification: May 18 , 2009
Workshop date: June 18, 2009

Organizers:

Matthias W. Seeger MPI Informatics / Saarland University, Saarbruecken
Suvrit Sra MPI Biological Cybernetics, Tuebingen
John P. Cunningham Stanford University (EE), Palo Alto

We acknowledge financial support through the PASCAL 2 Initiative of the European Union.

SMART workshop Call for Participation

CALL FOR PARTICIPATION

Statistical Multilingual Analysis for Retrieval and Translation – Barcelona 2009
http://patterns.enm.bris.ac.uk/smart-dissemination-workshop

Barcelona May 13, 2009
Venue: Aula Teleensenyament (Tele-teaching room) in building B3 of the Campus Nord of the UPC

A joint event of SMART project – PASCAL Network jointly-located with EAMT-2009

Co-organizers: Marco Turchi, Nello Cristianini, Xavier Carreras, Tijl de Bie

The aim of this workshop is to disseminate scientific results produced by the SMART project to the larger technical and scientific community working on Machine Translation. To facilitate this inter-exchange, it will be co-located with the EAMT 2009 – 13th Annual Conference of the European Association for Machine Translation that will be held May 14-15, 2009 Universitat Politècnica de Catalunya, Barcelona, Spain.

Conference web site: http://www.talp.cat/eamt09

Workshops page: http://www.talp.cat/eamt09/index.php/associated-workshops

Programme

Morning

9.30 – 10.00 Welcome, Nicola Cancedda, Xerox Research Centre Europe

10.00 – 11.00 Invited Talk: “Empirical Machine Translation and its Evaluation” – Jesus Gimenez, UPC

11.00 – 11.30 Coffee

11.30 – 12.00 – “Online learning for CAT applications” – Nicolo` Cesa-Bianchi, University of Milan

12.00 – 12.30 – “Sinuhe — Statistical Machine Translation with a Globally Trained Conditional Exponential Family Translation Model” – Matti T Kaariainen, University of Helsinki

12.30 – 1300 – “Large scale, maximum margin regression based, structural learning approach to phrase translations” – Sandor Szedmak, University of Southampton

LUNCH

Afternoon

14.00 – 14.30 “Learning to Translate: statistical and computational analysis” – Marco Turchi, University of Bristol

14.30 – 15.00 -“Detecting and exploiting Translation Direction” – Cyril Goutte, National Research Council – Canada

15.00 – 15.30 – “Multi-view CCA and regression CCA” – Blaz Fortuna, Jo¾ef Stefan Institute

Coffee

16.00 – 16.30 – “Large-Margin Structured Prediction via Linear Programming” – Zhuoran Wang, University College London

16.30 – 17.00 – “Confidence Estimation for Machine Translation” – Lucia Specia, Xerox Research Centre Europe

17.00 Closing Remarks

ABOUT THIS WORKSHOP

A joint event of SMART project – PASCAL Network

SMART (Statistical Multilingual Analysis for Retrieval and Translation, www.smart-project.eu) is a 3-year “Specific Target Research Project” (STReP) funded by the European Commission. SMART is
an attempt to address different problems of Machine Translation and Cross-Language Information Retrieval by the methods of modern Statistical Learning.

In the first two years of the project, the scientific focus has been on developing new and more effective statistical approaches while ensuring that existing know-how is duly taken into account. This was done by bringing together leading research institutions in Statistical Learning, Machine Translation and Textual Information Access.

PASCAL 2 (Pattern Analysis, Statistical Modelling and Computational Learning 2) is a 5-year “Network of Excellence” (NoE) funded by the European Commission, focusing on Machine Learning, Statistics and Optimization.

The aim of this workshop is to disseminate scientific results and share experiences produced by the SMART project to the larger technical and scientific community. The SMART consortium considers
this workshop to be a great opportunity for science investigations, creating both scientific and commercial opportunities as well as technological challenges to researchers.

Funded PhD post in data mining / machine learning – University of Bristol

Applications are invited for a fully funded PhD studentship (fees and stipend) in the Pattern Analysis and Intelligent Systems research group at the University of Bristol, UK.

Topic of the studentship:
“Statistical techniques for informative pattern mining in complex and structured data”
However, applicants interested in
“Machine Learning and Data Mining for Music Information Retrieval”
are also welcome to apply.

You will join a vibrant team working on the crossroads of data mining, machine learning, complexity science, and on applications in areas including bioinformatics, music information retrieval, web mining, news media analysis, and social network analysis.

The duration of the studentship is 3.5 years, and the starting date is 1 October 2009 or shortly after that (to be agreed).

The ideal candidate has a first class computer science / electrical engineering / mathematics / physics degree, with a strong background in mathematics as well as programming experience. (S)he is a loyal team player, and combines an interest in data mining and machine learning theory with a commitment to applying theoretical results in a real context, with a strong desire to make an impact.

Expressions of interest with a short CV, or any informal queries, should be sent to:
tijl.debie (at) bristol.ac.uk

Some links:
The Pattern Analysis and Intelligent Systems research group: http://patterns.enm.bris.ac.uk/,
part of the Intelligent Systems Lab: http://intelligentsystems.bristol.ac.uk/,
part of the University of Bristol: http://www.bristol.ac.uk/
part of the very enjoyable city of Bristol: http://en.wikipedia.org/wiki/Bristol

3 PhD positions in Natural Language Processing and Visualization

3 PhD positions in Natural Language Processing and Visualization

Institute for Natural Language Processing, University of Stuttgart
and
Computer Science Department, University of Stuttgart

The Institute for Natural Language Processing (IfNLP) and
the Computer Science Department of the University of
Stuttgart, Germany, invite applications for three PhD
positions.

IfNLP is one of the leading NLP research institutions
worldwide with four professors in different areas of NLP, a
research staff of 40 and an undergraduate program in NLP.
We offer the opportunity to work on cutting-edge research
projects in a dynamic and international research team and
up-to-date infrastructure and resources.

3 PhD positions are available immediately in two different
projects funded by Deutsche Forschungsgemeinschaft.

SEMISUPERVISED COREFERENCE RESOLUTION
2 PhD positions
Supervisors: Profs. Gunther Heidemann, Hans Kamp, and Hinrich Schuetze

This project will develop interactive visualization methods
for the semi-supervised annotation of large amounts of
training data for statistical coreference resolution.

INTERACTIVE VISUAL ANALYSIS OF COMPLEX INFORMATION SPACES
1 PhD position
Supervisor: Prof. Hinrich Schuetze

This project will integrate statistical NLP and
user-tailored interactive visual exploration methods and
apply them to the analysis of patents.

Candidates should have an excellent university degree in a
relevant field of study such as computational linguistics or
computer science.

To apply, send your CV in PDF format to sabine (at)
ims.uni-stuttgart.de by May 15, 2009. Please use the subject
line “PhD positions”. You should also provide two
references.

The University of Stuttgart is committed to increasing the
proportion of women in research and teaching. Qualified
women are encouraged to apply.

Call for Participation: ILP, MLG, SRL 2009

* SRL-2009 – International Workshop on Statistical Relational Learning
* ILP-2009 – 19th International Conference on Inductive Logic Programming
* MLG-2009 – 7th International Workshop on Mining and Learning with Graphs

**** Early registration closes May 15th ****

JOINT CALL FOR PAPERS

In 2009, three international conferences / workshops on learning from relational, graph-based and probabilistic knowledge will be co-located:
ILP-2009, the 19th International Conference on Inductive Logic Programming;
MLG-2009, the 7th International Workshop on Mining and Learning with Graphs;
SRL-2009, the International Workshop on Statistical Relational Learning.

These events are held as a Pascal 2 Network of Excellence event in Leuven, Belgium, on July 2-4, 2009. Time and location are highly compatible with the KDD-2009 conference in Paris, June 28 – July 1, at
only 2 hours train travel from Leuven.

AIM AND SCOPE

The ILP conference series has been the premier forum for work on logic-based approaches to learning for almost two decades. It has recently reached out to other forms of relational learning and to probabilistic approaches.

The MLG workshop series focuses on graph-based approaches to machine learning and data mining; since its conception in 2003, attendance numbers have consistently increased, and it now enjoys worldwide
recognition.

The SRL workshop series focuses on statistical inference and learning with relational and first-order logical representations. The combination of probability theory with relational (or first-order logic) knowledge
representations has been the subject of much recent research.

While the three series clearly have their own identity, there is a significant overlap in the topics covered by each of them. The aim of this co-location is to increase interaction between the three communities. The format of the joint event will stimulate such interaction by providing joint invited speakers and tutorials, joint sessions and poster sessions, and ample time and space for discussions in smaller groups, in addition to the regular programs of the three events.

Detailed calls for papers for the respective workshops, including submission instructions, are or will become available at http://www.cs.kuleuven.be/~dtai/sim/

Submissions to the events will be in the form of extended abstracts which can be accepted for either an oral or a poster presentation. The abstracts will be made available in an informal way (though more formal
post-conference publications are being considered as well, such as a post-conference proceedings for ILP and possibly special issues of journals for all events, more precise information on this will become
available at the website). As it is the goal that the very best work in the area be presented at the events, authors are explicitly encouraged to submit extended abstracts of high quality work in the area that has
recently been accepted or published at key venues.

IMPORTANT DATES

* April 3 Deadline for paper / abstract submissions
* April 30 Notification
* May 29 Deadline for camera ready copies
* July 2-4 Conference

ORGANIZATION

* ILP Program Chair: Luc De Raedt
* SRL Program Chairs: Pedro Domingos, Kristian Kersting
* MLG Program Chairs: Hendrik Blockeel, Karsten Borgwardt, Xifeng Yan
* General chair: Luc De Raedt

NIPS 2009 Call for Papers and Conference Poster Contest

NIPS 2009 PRELIMINARY CALL FOR PAPERS

Submissions are solicited for the Twenty-Third Annual Conference on Neural Information Processing Systems, an interdisciplinary conference that brings together researchers in all aspects of neural and statistical information processing and computation. The conference is a highly selective, single track meeting that includes invited talks as well as oral and poster presentations of refereed papers.
Submissions by authors who are new to NIPS are encouraged. Preceding the main conference will be one day of tutorials (December 7), and following will be two days of workshops at the Whistler/Blackcomb ski resort (December 11-12).

Deadline for Paper Submissions: Friday June 5, 2009,
23:59 Universal Standard Time (4:59pm Pacific Daylight Time).

A full description of the Call for Papers can be found here: http://nips.cc/Conferences/2009/CallForPapers

NIPS 2009 CONFERENCE POSTER CONTEST

This year, we’d like to capture the creativity of the NIPS community in 2009’s NIPS conference poster. The winner will receive full complimentary registration for the tutorials, conference, workshop, and bus transportation to Whistler. Please design a poster and upload it in PDF, PNG, or JPG format. This is open to any member of NIPS: students, postdocs, and faculty. The NIPS board will review and vote for the best one.

Upload your poster by July 15, 2009. Good luck and thank you for your valuable contributions. If you have any questions, please contact us at info@nips.cc.

Previous NIPS posters can be viewed here: http://nips.cc/Conferences/

Submission page: https://nips.cc/Conferences/2009/PosterContest/Upload/