Call for papers – Appel à communications – JFPDA’13

JFPDA is the French Workshop on Reinforcement Learning and
Decision Making. The event is mainly French-speaking, but not
only

—————–

JFPDA’13
8èmes Journées Francophones sur la Planification, la Décision et l’Apprentissage pour la conduite de systèmes, Lille, 01-02 juillet 2013.
http://pfia2013.univ-lille1.fr/doku.php?id=fr:jfpda

Présentation
Les Journées Francophones sur la Planification, la Décision et l’Apprentissage pour la conduite des systèmes (JFPDA) ont pour but de rassembler la communauté de chercheurs francophones travaillant sur les problèmes d’intelligence artificielle, d’apprentissage par renforcement, de programmation dynamique et de tous les domaines liés à la prise de décision séquentielle et à la planification. Les travaux présentés traitent aussi bien d’aspects purement théoriques que de l’application de ces méthodes à la conduite de systèmes virtuels (jeux, simulateurs) et réels (robots, drones). Ces journées sont aussi l’occasion de présenter des travaux en cours de la part de doctorants, postdoctorants et chercheurs confirmés dans un cadre laissant une large place à la discussion constructive et bienveillante.
Après Toulouse (2006), Grenoble (2007), Metz (2008), Paris (2009), Besançon (2010), Rouen (2011) et Nancy (2012), les journées se tiendront en 2013 à Lille, dans le cadre de la plate-forme AFIA.

Invitée
• Joelle Pineau (McGill University, Montréal, Canada)

Thèmes principaux
• Processus décisionnels de Markov, totalement ou partiellement observables, factorisés ou hiérarchiques, centralisés ou décentralisés
• Programmation Dynamique approchée (ADP), apprentissage par renforcement (RL)
• RL Bayésien, RL inverse, RL batch, RL multi-agents, RL multi-objectifs
• Convergence et bornes sur les performances des algorithmes RL/ADP
• Complexité en RL/ADP
• Apprentissage statistique, bornes PAC en RL/ADP
• Méthodes de Monte Carlo and quasi Monte Carlo
• Recherche directe de politiques, architectures acteur-critique
• Apprentissage de fonctions de valeurs, généralisation, représentations parcimonieuses, méthodes à base de noyaux en RL/ADP
• Planification classique, planification temporelle
• Replanification, planification en ligne
• Contrôle de systèmes continus ou discrets, réels ou simulés, mono ou multi-agents
• Approches d’inspiration biologique
• Applications et confrontations au monde réel.

Appel à communications
Les travaux soumis aux JFPDA peuvent prendre différentes formes :
• Résumé étendu (6 pages maximum, avec vocation à être présenté en poster),
• Article long original,
• Article long soumis ou accepté dans un atelier ou une conférence internationale.
Dans tous les cas, la version finale pourra être en anglais ou en français et devra comporter 16 pages au maximum dans le format donné ci-dessous. Les versions finales des papiers seront disponibles via des liens url qui seront communiqués par les auteurs eux-mêmes et rassemblés sur cette page web.
Le comité de programme proposera pour chaque travail soit une présentation en session orale (avec la possibilité de présenter en poster également si les auteurs le souhaitent), soit uniquement une présentation en session poster. Cela permettra à tous les auteurs de concourir pour le prix (symbolique) du meilleur poster (voir section “Prix du meilleur poster”).

Prix du meilleur poster
Un prix symbolique sera attribué au meilleur poster. Plus d’informations seront disponibles prochainement sur les modalités de l’attribution de ce prix.

Prix d’équipe
Un prix symbolique sera également attribué à l’équipe de recherche ayant le plus grand nombre de travaux acceptés aux JFPDA 2013 ! Les modalités de ce prix seront également précisées ultérieurement.

Dates clés
Date limite de soumission des papiers : 01/04/2013
Notification aux auteurs : 15/05/2013
Date limite de soumission de la version finale : 01/06/2013
Conférence : du 01/07/2013 au 02/07/2013

Soumission d’articles
Depuis le 01 mars 2013, vous pouvez soumettre vos travaux à l’adresse suivante:
https://www.easychair.org/conferences/?conf=jfpda2013
Le format de soumission est simple : on attend un fichier au format pdf exclusivement, idéalement créé avec pdfLaTeX et le style suivant.

Comité scientifique
Président du comité de programme
Rémi Munos

Membres du comité de programme
Marta Soare
Raphael Fonteneau
Michal Valko
Alessandro Lazaric

Autres membres du comité scientifique
(En cours de construction)
Olivier Buffet (Inria – Loria, Nancy)
Lucian Busoniu (CNRS – Université de Lorraine – CRAN, Nancy)
Olivier Cappé (CNRS – Telecom ParisTech, Paris)
Yann Chevaleyre (Université Paris Dauphine – LAMSADE, Paris)
Rémi Coulom (Université Lille 3 – Inria, Lille)
Boris Defourny (Princeton University, Princeton, USA)
Christos Dimitrakakis (Ecole Polytechnique Fédérale de Lausanne, Suisse)
Alain Dutech (Inria – Loria, Nancy)
Damien Ernst (Université de Liège, Belgique)
Patrick Fabiani (ONERA, Toulouse)
Humbert Fiorino (Université Joseph Fourier – LIG, Grenoble)
Aurélien Garivier (Université Paul Sabatier – IMT, Toulouse)
Matthieu Geist (SUPELEC, Metz)
Mohammad Ghavamzadeh (Inria, Lille)
Nathaniel Korda (Inria, Lille)
Guillaume Laurent (École Nationale Supérieure de Mécanique et des Microtechniques – FEMTO, Besançon)
Manuel Lopes (Inria, Bordeaux)
Francis Maes (Katholieke Universiteit Leuven, Belgique)
Odalric-Ambrym Maillard (Israel Institute of Technology, Haifa, Israel)
Laetitia Matignon (Université Claude Bernard Lyon 1 – LIRIS, Lyon)
Cyril Pain-Barre (Aix-Marseille Université – LSIS, Aix-en-Provence)
Olivier Pietquin (SUPELEC – CNRS – GeorgiaTech, Metz)
Joëlle Pineau (McGill University, Montréal, Canada)
Cédric Pralet (Onera – IRIT, Toulouse)
Philippe Preux (Université Lille 3 – LIFL – Inria, Lille)
Emmanuel Rachelson (ISAE, Toulouse)
Daniil Ryabko (Inria, Lille)
Régis Sabbadin (INRA, Toulouse)
Olivier Sigaud (Université Pierre et Marie Curie, Paris)
Balazs Szorenyi (Inria, Lille)
Florent Teichteil-Königsbuch (Onera, Toulouse)
Olivier Teytaud (Inria, Saclay)
Vincent Thomas (Université de Lorraine – Loria, Nancy)
Gérard Verfaillie (Onera, Toulouse)
Thierry Vidal (Ecole Nationale d’Ingénieurs de Tarbes)
Vincent Vidal (Onera, Toulouse)
Paul Weng (Université Pierre et Marie Curie – LIP6, Paris)
Bruno Zanuttini (Université de Caen Basse-Normandie – GREYC, Caen)

FGVC2 workshop at CVPR 2013

2nd Workshop on Fine-Grained Visual Categorization (FGVC^2)
In Conjunction with CVPR 2013

Call for Abstracts/Posters
PDF Version: http://fgvc.org/FGVC2_CallForPosters.pdf

OVERVIEW:
————
The purpose of this workshop is to bring together researchers to
explore visual recognition across the continuum between basic level
categorization (object recognition) and identification of individuals (face
recognition, biometrics) within a category population.

SCOPE:
———-
Topics of interest include the following:
• Novel datasets and data collection strategies for fine-grained categorization
• Appropriate error metrics for fine-grained categorization
• Embedding human experts’ knowledge into computational models
• Fine-grained categorization with humans in the loop
• Transfer-learning from known to novel subcategories. Zero/one-shot recognition
• Domain-specific techniques that generalize to various other domains
• Attribute-based techniques for fine-grained categorization
• Using taxonomies to improve fine-grained categorization
• Part-sharing models for categorization/recognition
• Unsupervised subcategory discovery
• Learning of discriminative features for fine-grained categorization
• Multimodal (e.g. combined audio/video) techniques for fine-grained
categorization
• Fine-grained categorization systems deployed in practice

Abstract/Poster Submission:
——————————-
We invite submission of 1.5-2 page extended abstracts (using the CVPR 2013
format) describing work in the domains suggested above or in closely-related
areas. Accepted submissions will be presented as posters at the workshop.
Authors may submit a draft of their poster as an optional third page. The
extended abstract and poster sketch should be submitted as a single PDF file
with no more than 3 pages. Reviewing of abstract submissions will be
double-blind. The purpose of this workshop is not as a venue for publication,
so much as a place to gather together those in the community working on or
interested in FGVC. Submissions of work which has been previously published,
including papers accepted to the main CVPR 2013 conference are allowed.

Abstract/Poster Submission Deadline: April 19, 2013
Notification of Acceptance: May 15, 2013
Workshop date: Friday, June 28, 2013

Submission Website: https://cmt.research.microsoft.com/FGVC2013/
FGVC2 Website: http://www.fgvc.org/

Workshop Organizers:
————————
• Ryan Farrell (ICSI, UC Berkeley)
• Steve Branson (Caltech)
• Neeraj Kumar (University of Washington)
• Anelia Angelova (NEC Labs America)
• Florent Perronnin (Xerox Research)

=============================================
| **Dataset Challenge**: As a part of the FGVC workshop, we will also be |
| conducting a fine-grained recognition competition, similar to the PASCAL |
| VOC and ImageNet challenges. The challenge dataset and details will be |
| distributed shortly in a separate call for participation. |
=============================================

Researcher position, Statistical Machine Translation – Xerox Grenoble, France

Researcher, Statistical Machine Translation

The Machine Learning for Document Access and Translation group of the Xerox Research Centre Europe conducts research in Statistical Machine Translation and Information Retrieval, Categorization and Clustering using advanced machine learning methods.

We are opening a position for a researcher with a background in Statistical Machine Translation to support our participation in the EU-funded project TransLectures (www.translectures.eu).

Required experience and qualifications:

– PhD in computer science or computational linguistics, with focus on
statistical methods
– Experience with Statistical Machine Translation.
– Good publication record and evidence of implementing systems.
– A good command of English, as well as open-mindedness and the will
to collaborate within a team.
– Acquaintance with Spoken Language Translation is a plus.

Preferred starting date: July 2013

Contract duration: 18 months

Application instructions

Please email your CV and covering letter, with message subject “Statistical Machine Translation Researcher” to xrce-candidates and to Nicola.Cancedda at xrce.xerox.com. Inquiries can be sent to Nicola.Cancedda at xrce.xerox.com.

XRCE is a highly innovative place and we strongly encourage publication and interaction with the scientific community.

Job announcement URL:

http://www-int.xrce.xerox.com/About-XRCE/Career-opportunities/Researcher-Statistical-Machine-Translation

Second Call for papers SISAP 2013

===========================
SISAP 2013 – SECOND CALL FOR PAPERS
===========================

We apologize if you receive duplicates of this CFP.
Please feel free to distribute it to those who might be interested.

SISAP 2013: 6th International Conference on Similarity Search and Applications
October 2-4, 2013
A Coruna, Spain

Web site: http://www.sisap.org/2013
Facebook: http://www.facebook.com/sisap2013
Twitter: http://twitter.com/sisap2013,

Scope

The International Conference on Similarity Search and Applications (SISAP) is an annual forum for researchers and application developers in the area of similarity data management. It aims at the technological problems shared by numerous application domains, such as data mining, information retrieval, computer vision, pattern recognition, computational biology, geography, biometrics, machine learning, and many others that need similarity searching as a necessary supporting service.

The SISAP initiative (www.sisap.org) aims to become a forum to exchange real-world, challenging and innovative examples of applications, new indexing techniques, common test-beds and benchmarks, source code and up-to-date literature through its web page, serving the similarity search community. Traditionally, SISAP puts emphasis on the distance-based searching, but in general the conference concerns both the effectiveness and efficiency aspects of any similarity search problem.

The series started in 2008 as a workshop and has developed over the years into an international conference with Lecture Notes in Computer Science (LNCS) proceedings. As in previous editions, a small selection of the best papers presented at the conference will be recommended for inclusion in a special issue of Information Systems. In October 2013, SISAP will take place in A Coruna, Spain.

Keynote Speakers

Ricardo Baeza-Yates (VP of Yahoo! Research for Europe, Middle East and Latin America)
Jiri Matas (Center for Machine Perception, Czech Technical University)

Topics of interest

The specific topics include, but are not limited to:
Similarity queries – k-NN, range, reverse NN, top-k, etc.
Similarity operations – joins, ranking, classification, categorization, filtering, etc.
Evaluation techniques for similarity queries and operations
Merging/combining multiple similarity modalities
Cost models and analysis for similarity data processing
Scalability issues and high-performance similarity data management
Feature extraction for similarity-based data findability
Test collections and benchmarks
Performance studies, benchmarks, and comparisons
Similarity Search over outsourced data repositories
Similarity search cloud services
Languages for similarity databases
New modes of similarity for complex data understanding
Applications of similarity-based operations
Image, video, voice, and music (multimedia) retrieval systems
Similarity for forensics and security

Important Dates

Abstract submission: May, 3rd, 2013
Paper submission: May, 10th, 2013
Notification: June, 21st, 2013
Final version: July, 10th, 2013
Conference: October 2-4, 2013

Submission guidelines

Papers submitted to SISAP 2013 must be written in English and formatted according to the LNCS guidelines. Full papers can be up to 12 pages, while short papers, case-studies/applications, and demos can be up to 6 pages (read below for types of contribution). By submitting a paper, its authors commit to have the paper presented at the conference by at least one of them if the paper is accepted.

Contributions

Authors are invited to submit previously unpublished papers on their research in the area of similarity search and applications. Papers should present original research contributions which bring out the importance of algorithms to applications. SISAP submissions can be of three kinds:

Research papers (full and short): SISAP accepts both full (12 pages) and short papers (6 pages). The full papers are expected to be descriptions of complete technical work, while the short papers will describe interesting, innovative ideas, which nevertheless require more work to mature – vision papers should also be submitted as short papers. All papers, regardless of size, will be given an entry in the conference proceedings.

Case-studies and applications: Submissions describe applications of existing similarity search technologies to interesting problems, including a description of the encountered challenges, how they were overcome, and the lessons learned. All papers on this track will be given an entry in the conference proceedings and a presentation slot, though the presentation slot duration may be shorter than for full research papers.

Demonstration papers: Submissions should provide the motivation for the demonstrated concepts, the information about the technology and the system to be demonstrated (including a system description, functionality and figures when applicable), and should state the significance of the contribution. Evaluation criteria for the demonstration proposals include: the novelty, the technical advances and challenges, and the overall practical attractiveness of the demonstrated system. Demonstration papers will also be given an entry in the conference proceedings – online demos are expected at the conference.

Program comittee chairs

Pavel Zezula, Masaryk University, Czech Republic
Nieves R. Brisaboa, Universidade da Coruna, Spain

Program comittee members

Giuseppe Amato, ISTI – Istituto di Scienza e Tecnologia dell’Informazione, Italy
Laurent Amsaleg, IRISA – Institut de Recherche en Informatique et Systemes Aleatoires, France
Benjamin Bustos, Universidad de Chile, Chile
Edgar Chavez, Universidad Michoacana, Mexico
Paolo Ciaccia, University of Bologna, Italy
Richard Connor, Strathclyde University, UK
Andrea Esuli, Istituto di Scienza e Tecnologie dell’Informazione, Italy
Rosalba Giugno, University of Catania, Italy
Michael Houle, National Institute of Informatics, Japan
Alexis Joly, INRIA, France
Daniel Keim, Universitat Konstanz, Germany
Eamonn Keogh, University of California – Riverside, USA
Magnus Lie Hetland, Norwegian University of Science and Technology, Norway
Yannis Manolopoulos, Aristotle University of Thessaloniki, Greece
Rui Mao, Shenzhen University, China
Luisa Mico, University of Alicante, Spain
Henning Muller, University of Applied Sciences Western Switzerland, Switzerland
Gonzalo Navarro, Universidad de Chile, Chile
Arlindo Oliveira, Lisbon Technical University, Portugal
Jose Oncina, University of Alicante, Spain
Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece
Marco Patella, University of Bologna, Italy
Vladimir Pestov, University of Ottawa, Canada
Matthias Renz, Ludwig-Maximilians-Universitat Munchen, Germany
Hanan Samet, University of Maryland, USA
Tomas Skopal, Charles University in Prague, Czech Republic
Bjorn Thor Jonsson, Reykjavik University, Iceland

Local organization

Nieves R. Brisaboa, Universidade da Coruna, Spain
Oscar Pedreira, Universidade da Coruna, Spain

PASCAL2 IASD challenge: Deadline extension

=================================================================
Interactive Annotation of Sequential Data (IASD)
PASCAL2 challenge
http://translectures.eu/iasd
=================================================================
— Please, accept our apologies in case of multiple receptions —

*** New First Phase Deadline: March 25 ***

Dear colleagues,

We are pleased to announce an extension of the Interactive Annotation
of Sequential Data (IASD) PASCAL2 challenge deadlines. The aim of the
IASD challenge is to explore innovative, cost-effective solutions for
generating accurate transcriptions for video lectures from
VideoLectures.NET, and, at a more general level, speech-like
sequential data. The focus is not on developing advanced speech
recognition techniques, so much as on the study of techniques for
interacting intelligently with users. These techniques should seek to
optimise the trade-off between user effort and accuracy, in such a way
that the winning approaches are those reaching the top-3 accuracy with
minimum feedback.

Important Dates (extended):

Feb 12, 2013 – First challenge phase starts.
Mar 25, 2013 – First phase ends: selection of the 3 best systems.
Mar 26, 2013 – Second phase starts (for the 3 best systems only).
Apr 5, 2013 – Second phase ends: winners annouced and ranked.
Apr 6, 2013 – Reports deadline for the winners.

Presentation and awards:

The winners will be invited to present their systems at the joint
EUCOGIII/PASCAL meeting in Palma de Mallorca on April 11, 2013, with
travel costs covered by the meeting organisation. Winners attending
the meeting will be awarded with the following net prizes (after
taxes):

1st prize: €1000
2nd prize: €600
3rd prize: €300

You will find a detailed description of the challenge, data and
evaluation methodology at:

http://translectures.eu/iasd

Challenge Organizers:

Nicolas Serrano, Jesus Andres, Alfons Juan (UPV)
John Shawe-Taylor, Davor Orlic (K4A)
Mitja Jermol (JSI)

Challenge sponsors:

PASCAL2 Network (http://www.pascal-network.org)
EUCOGIII Network (http://www.eucognition.org)
transLectures project (http://translectures.eu)
Universitat Politecnica de Valencia (http://www.upv.es/index-en.html)
Knowledge for all (http://www.k4all.org)
Jožef Stefan Institute (http://www.ijs.si/ijsw/JSI)

PhD studentship in computer vision, eye-tracking, and natural language, University of Edinburgh

University of Edinburgh
School of Informatics

PHD STUDENTSHIP IN COMPUTER VISION, EYE-TRACKING, AND NATURAL LANGUAGE

Applications are invited for a fully funded, three-year PhD studentship that combines ideas from computer vision, eye-tracking research, and natural language processing. The aim of the PhD project is to develop techniques for using human fixation data as recorded by an eye-tracker to train computer vision models, thus reducing the need for manual annotation. This approach will be augmented to exploit textual data (e.g., image captions) to improve object labeling. Another project aim is to crowd-source the eye-tracking data, e.g., through the use of webcams.

Applicants for the studentship must have:

* Strong undergraduate degree in computer science or a related
discipline

* Excellent programming skills

* Solid mathematical foundations (especially linear algebra and
probability theory)

* Fluency in English, both written and spoken

* UK or EU nationality — this is mandatory; applicants of other
nationalities will not be considered

* Master’s degree in a relevant area is desirable

* Experience in computer vision, machine learning, natural
language processing, or eye-tracking is desirable

The School of Informatics at Edinburgh is one of the top-ranked computer science departments in Europe and offers an exciting, interdisciplinary research environment. Edinburgh is a beautiful historic city with a high quality of life.

Starting date: September 2013 as soon as possible after that.

The PhD work will be carried out under the supervision of Dr. Vittorio Ferrari and Dr. Frank Keller, whose research interests can be found at:

http://groups.inf.ed.ac.uk/calvin/
http://homepages.inf.ed.ac.uk/keller/

For pre-screening, please send applications to the email address below, including:

* Full CV

* Full transcripts of both undergraduate and Master’s degree (if
applicable); this studentship requires high grades, especially
in mathematics and programming courses

* The names and email addresses of two referees

* List of publications, if you have prior research experience

Contact: Vittorio Ferrari, vferrari@staffmail.ed.ac.uk

Deadline: 25 April 2013

BioASQ challenge on large-scale biomedical semantic indexing and question answering

BioASQ challenge on large-scale biomedical semantic indexing and question
answering
(BioASQ workshop to be collocated with CLEF 2013 in Valencia, Spain on
September 27, 2013)

Web site: http://bioasq.org/
twitter: https://twitter.com/bioasq

The BioASQ challenge aims to push for a solution to the information access
problem of biomedical experts. It will evaluate the ability of systems to
perform various tasks in the biomedical QA process:
1. large-scale classification of biomedical documents onto ontology concepts
(semantic indexing),
2. classification of biomedical questions onto relevant concepts,
3. retrieval of relevant document snippets, concepts and knowledge base
triples, and
4. delivery of the retrieved information in a concise and
user-understandable form.

In particular, the challenge will comprise two main tasks:

Task 1a. Large-scale online biomedical semantic indexing
Large-scale semantic indexing will be evaluated on the whole of PubMed. In
particular, participants will be asked to classify incoming documents before
the human curators do:
* BioASQ will distribute new unclassified PubMed documents.
* Participants will have a limited response time to attach MeSH terms.

Task 1a will run for three consecutive periods (batches) of 6 weeks each.
The first batch will start on April 15, 2013. Separate winners will be
announced for each batch. Participation in the task can be partial, i.e. in
some of the batches.

Task 1b. Biomedical semantic QA
The systems will be evaluated against gold answers created by a team of
biomedical experts. The task will run in two phases:
In Phase A:
* BioASQ will transmit simultaneously questions from the benchmark.
* Participants will have limited time to respond with concepts, snippets,
triples.
In Phase B:
* BioASQ will distribute questions + concepts, snippets, triples.
* Participants will respond with facts, summaries, etc.

The two phases will run consecutively, i.e. Phase B will start after the end
of phase A. Phase A will start on June 3, 2013. Separate winners will be
announced for each phase and each task target, i.e. concepts, snippets,
triples, etc. Participation in the task can be partial, i.e. in one of the
two phases and only for some of the targets.

Prizes will be awarded to the winners. Details about the prizes will be
announced on the Web site of the challenge.

Important dates:
March 18, 2013: Training data available for task 1a. Dry-run data available
for task 1b.
April 15, 2013: Start of task 1a.
June 3, 2013: Start of task 1b.
July 15, 2013: Submission of papers for BioASQ workshop
August 30, 2013: End of challenge
September 27, 2013: BioASQ workshop, collocated with CLEF 2013

The BioASQ challenge and workshop are organised by the BioASQ project,
supported by the European Commission within the 7th Framework Programme
(Grant Agreement No. 318652).

CFP: ICML 2013 Workshop on Spectral Learning

Call for Papers: Workshop on Spectral Learning — @ICML2013
June 20 or 21, Atlanta (GA), USA
Website: http://sites.google.com/site/spectrallearningworkshop/

Many problems in machine learning involve collecting high-dimensional multivariate observations or sequences of observations, and then fitting a compact model which explains these observations. Recently, linear algebra techniques have given a fundamentally different perspective on how to fit and perform inference in these models. Exploiting the underlying spectral properties of the model parameters has led to fast, provably consistent methods for parameter learning that stand in contrast to previous approaches, such as Expectation Maximization, which suffer from slow convergence and issues related to local optima.

In the past several years, these spectral learning algorithms have become increasingly popular. They have been applied to learn the structure and parameters of many models including predictive state representations, finite state transducers, hidden Markov models, latent trees, latent junction trees, probabilistic context free grammars, and mixture/admixture models. Spectral learning algorithms have also been applied to a wide range of application domains including system identification, video modeling, speech modeling, robotics, and natural language processing.

The focus of this workshop will be on spectral learning algorithms, broadly construed as any method that fits a model by way of a spectral decomposition of moments of (features of) observations. We would like the workshop to be as inclusive as possible and encourage paper submissions and participation from a wide range of research related to this focus. This includes (but is not limited to):

* Linear-algebraic methods for estimation and inference in probabilistic models and weighted automata/operator models
* Spectral approaches to dimension reduction (e.g., with applications in estimating mixture models)
* Method-of-moment estimation via higher-order tensor decompositions
* Spectral graph theory and applications in clustering and learning on manifolds
* Domain-specific aspects of using spectral approaches in applications

Submitted papers should be in the ICML 2013 format with a maximum of 4 pages (not including references). Please e-mail your submission to spectralicml2013@gmail.com with the subject line “Submission to Spectral Learning Workshop”. Contributions will be considered for both short talks and poster presentations.

Concurrent submissions to the workshop and the main conference (or other conferences) are permitted.

Important dates:

* Submission deadline: April 6, 2013
* Notification of acceptance: April 20, 2013 (tentative)
* Workshop: June 20 or 21, 2013

Organizers:

* Byron Boots (University of Washington)
* Daniel Hsu (Microsoft Research New England)
* Borja Balle (Universitat Politècnica de Catalunya)
* Ankur Parikh (Carnegie Mellon University)

PostDoc in Dimensionality Reduction and Information Visualization at UCLouvain

The Université catholique de Louvain invites applications for a 2-year postdoctoral position in Machine Learning/Information Visualisation, beginning July 1, 2013.

The visual interpretation of data is an essential step to guide any further processing or decision making. Data visualization is tackled independently from two different angles in the scientific community. The domain of machine learning addresses mainly statistical, mathematical, and algorithmic aspects with dimensionality reduction (DR) techniques, whereas the field of information visualization focuses on the interaction with the user (man-computer interface, visual efficacy, user-friendliness). In this context, the project aims at bridging the two approaches. More specifically, the project intends to import the concepts of interactivity and controllability from the field of information visualization and to integrate them in advanced DR techniques in order to improve their acceptance by users and broaden their range of application.

The successful applicant will hold a Ph.D. degree delivered not earlier than July 1, 2007, and must not have the Belgian nationality. In addition, the candidate must not have lived in Belgium for more than 2 years since July 1, 2010. The net salary after deduction of taxes and social security is about 26000 euros per year, or more, depending on seniority.

Applicants should be knowledgeable in machine learning, data mining, information visualisation, with a particular interest in manifold learning, dimensionality reduction and information retrieval. Applicants should have a strong background in computer science and applied mathematics.

A working knowledge of English language is mandatory. French is an optional asset.

Working location will be Louvain-la-Neuve, a lively pedestrian town in the suburbs of Brussels, where most of the Université catholique de Louvain is located. The work will be carried out in collaboration with Profs. John A. Lee
(http://scholar.google.be/citations?user=ZopTupcAAAAJ) and Michel Verleysen (http://perso.uclouvain.be/michel.verleysen/), in the ICTEAM institute (http://www.uclouvain.be/en-icteam.html).

Application procedure: Interested individuals should send a CV, a brief statement of research and development interests (max. 1 page), and the names and contact details of two references by e-mail to John Lee
(john.lee@uclouvain.be) with subject “Postdoc DRedVis”.

Candidates interested should send their application before March 15th, 2013; we reserve the right to accept late applications. The position will be available for an initial period of 1 year, with possible one-year extension after mid-term evaluation.

Postdoctoral Position in Machine Learning at INRIA Lille – Team SequeL

Applications are invited for a Postdoctoral position on the general area of “Sequential Decision-making in Online Marketing” at INRIA Lille – Team SequeL. Below is the detail of this call.

—

Title: Sequential Decision-making in Online Marketing: Optimizing the Lifetime Value of Customers

Keywords: sequential decision-making, reinforcement learning, online marketing and advertising, exploration/exploitation dilemma, bandit algorithms, adaptive resource allocation, regret minimization, optimization

Research Program:

The candidate is expected to conduct research on both theoretical and applied aspects of the problem of “Sequential Decision-making in Online Marketing” and related problems (see the description below), collaborate with researchers and Ph.D. students at INRIA and outside, and publish the results of her/his research in conferences and journals. The candidate will work with Mohammad Ghavamzadeh (http://chercheurs.lille.inria.fr/~ghavamza) and other researchers at Team SequeL (https://sequel.lille.inria.fr).

With the growth of online marketing, customers visit websites on a regular basis (sometimes daily in the case of banking, e-commerce, and media websites), and at each visit a stream of interactions occurs between the company (promotion, advertisement, email) and a customer (purchase, click on an ad, signing up for a newsletter). This creates many opportunities for a company to reach a customer and make decisions to optimize its objective function (revenue, customer satisfaction, etc.). Today, these marketing decisions are mainly made in a myopic way (mainly using contextual bandit algorithms) without taking into account the lifetime value of the customer. This myopic approach assumes that a decision made by the company does not affect the customer’s future interactions with the company. However, in many applications the sequential nature of the problem is significant (having a long-term relation with customers is important for the company), and thus, myopic decisions have po!
or performance in these problems. This creates an opportunity for reinforcement learning (RL) techniques to play a significant role in this emerging field.

The objective of this research program is to answer fundamental questions related to the use of myopic (contextual bandit algorithms) and non-myopic (sequential decision-making and RL algorithms) decision-making methods in the growing field of online marketing. Questions such as

– Feature selection and dealing with high dimensional data: discovering the right representation for the problem at hand and dealing with the size and dimensionality of the data are among the most important questions in these applications. The size and dimensionality of the data create difficulties for the standard sequential decision-making algorithms. This is closely related to another growing research direction: sequential decision-making with big data.

– Off-policy evaluation: how to evaluate a policy learned from a batch of historical data generated with a different policy (usually the company’s policy) with minimum interaction with the real-world environment. Running a strategy on the real system can be costly: it usually takes a long time to have a reasonable evaluation of its quality and more importantly is the risk of a big loss in case the strategy is not good.

– Discovering patterns in the sales funnel in order to find strategies to direct more customers through the funnel to the final sale.

– Dealing with the non-stationarity, mainly caused by change in the preferences of the customer, arrival and departure of customers, evolution of webpage contents, etc., and delayed feedback (significant delay between an action taken by the marketer and its effects on the customer) in the online marketing applications.

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Requirements:

The applicant will have a Ph.D. degree (by the starting date of the postdoctoral position) in Computer Science, Statistics, or related fields, with background in reinforcement learning, bandit algorithms, statistics, and optimization. Programming skills will be considered as a plus. The working language of the group is English, so the candidate is expected to have good communication skills in English.

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About INRIA and Team SequeL:

SequeL (https://sequel.lille.inria.fr) is one of the most dynamic teams at INRIA (http://www.inria.fr), with over 25 researchers and Ph.D. students working on several aspects of machine learning from theory to application, including statistical learning, reinforcement learning, and sequential decision-making. The SequeL team is involved in national and European research projects and has collaboration with international research groups. This allows the postdoctoral candidate to collaborate with leading researchers in the field at top universities in Europe and North America such as University College of London (UCL), University of Alberta, and McGill University. Moreover, in this project there is the possibility of close collaboration with an online marketing company in the US. Lille is the capital of the north of France, a metropolis with over one million inhabitants, and with excellent train connection to Brussels (30min), Paris (1h) and London (1h30).

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Benefits:

– Duration: 16 months – starting date of the contract : November 1, 2013
– Salary: 2620.84 Euros gross/month monthly salary
– Monthly salary after taxes: around 2138 Euros (medical insurance included)
– Possibility of French courses
– Help for housing
– Participation for transportation
– Scientific Resident card and help for husband/wife visa

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Application Submission:

The application should include a brief description of the applicant’s research interests and past experience, plus a CV that contains her/his degrees, GPAs, relevant publications, name and contact information of up to three references, and other relevant documents. Please send your application to mohammad.ghavamzadeh@inria.fr. The deadline for the application is April 15 but the applicants are encouraged to submit their application as soon as possible.

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This call has also been posted on

1) my webpage at

http://chercheurs.lille.inria.fr/~ghavamza/postdoc-ad-2013.html

2) the INRIA website at:

http://www.inria.fr/institut/recrutement-metiers/offres/post-doctorat/campagne-2013/%28view%29/details.html?id=PGTFK026203F3VBQB6G68LONZ&LOV5=4508&LG=FR&Resultsperpage=20&nPostingID=7352&nPostingTargetID=12788&option=52&sort=DESC&nDepartmentID=19