CFP SI Modality and Negation in Computational Linguistics

—————————————————

CALL FOR PAPERS

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A Special Issue of the Computational Linguistics Journal
on
Modality and Negation

http://cljournal.org/specials/modality-and-polarity.html
———————————————————-

Computational linguistics has seen achievements in handling language at different levels of linguistic abstraction, from tokenization to semantic role labeling. Given a sentence, systems can more or less reliably determine who does what to whom when and where. However, texts do not always express factual information; on the contrary, language is often used to express uncertainty, opinion, evaluation, or doubt. Accordingly, computational linguistics has started to take into account the subjective aspects of language. There is now research that focuses also on determining who states that someone does something somewhere at a certain point in time (perspective) and based on what evidence (evidentiality), how certain someone is about stating something (certainty), the truth value of the facts being stated (negation), or the subjective evaluation of these facts (positive/negative opinion).

Linguistic phenomena such as modality and negation allow the expression of subjective aspects of meaning. Modality and negation are two information-level concepts that are well described from a philosophical perspective. Modality (Palmer 1986) is related to the attitude of the speaker towards her statements in terms of degree of certainty, reliability, subjectivity, sources of information, and perspective. It is related to other concepts like hedging (Hyland 1998), evidentiality (Aikhenvald 2004), uncertainty (Rubin et al. 2005), and factuality (Saurí 2008). Negation (Tottie 1991, Horn 2001) is used to position information as a counterfact, a fact that does not hold in the world. Both modality and negation are complex linguistic phenomena that are challenging both from a theoretical and a computational point of view. Their complexity is due to the fact that both phenomena interact with each other (de Haan 1997) and with other aspects of the linguistic context, such as mood, tense, and lexis. While modality and negation tend to be lexically marked, the class of markers is relatively large and heterogeneous. For example, while negation words such as “not” are clear indicators of negation, other terms such as modals, adverbs, conjunctions and multi-word expressions can also express negation and subjectivity. Moreover, processing modality and negation involves disambiguating the markers and determining their scope.

The treatment of modality and negation is very relevant for all NLP applications that involve deep text understanding. This includes applications that need to discriminate between factual and non-factual information (uncertain facts, opinions, attitudes, emotions, and beliefs), such as information extraction, opinion mining, sentiment analysis, text mining, and question answering, as well as other applications that process the meaning of texts, such as recognizing textual entailment, paraphrasing, and summarization. Hence, the adequate modeling of these phenomena is of crucial importance to the NLP community as a whole. While the area is still relatively new compared to areas like machine translation, parsing or semantic role labeling, it is now growing quickly.

TOPICS

For this special issue we solicit full-length article submissions describing innovative and challenging research on aspects of the computational modelling and processing of modality and negation. We specifically invite submissions that take into account linguistic aspects of the phenomena and bring a theoretical basis to research on computing the factuality and certainty of the events in a statement, finding the source and evidence for the statement of a fact, and determining whether a statement has a truth value. We encourage submissions that have a substantial analysis component, in the form of an analysis of the task and data and/or an error analysis of the proposed method. Submissions can address aspects of either modality or negation or both, provided that they lead to an enhanced understanding of the phenomena, as opposed to a straightforward engineering solution.

Possible topics include, but are not limited to:

– Linguistically informed modelling of modality and negation for NLP
– Analysis of the relevant information/knowledge involved in processing modality and negation
– The computational complexity of processing modality and negation
– Novel machine learning approaches for learning modality and negation
– Processing modality and negation across domains and genres
– The interaction of modality and negation for determining the factuality of events
– The influence of the linguistic context on the processing of modality and negation
– Evaluation of systems: metrics and application-based evaluation

EXPRESSION OF INTEREST

If you are considering submitting an article to this special issue, please send an expression of interest to the Guest Editors (roser.morante(at)ua.ac.be, csporled@coli.uni-sb.de) before the 10th December, 2010. Expressions of interest are not binding. Please use subject line “EoI CL SI Modality and Negation”, and include a brief description of your potential submission.

IMPORTANT DATES

Call for papers: 10 November 2010
Expressions of interest: 10 December 2010
Submission of full articles: 10 March 2011
Preliminary decisions to authors: 31 June 2011
Submission of revised articles: 30 August 2011
Final decisions to authors: 18 October 2011
Final versions due from authors: 1 November 2011

SUBMISSION INSTRUCTIONS

Articles submitted to this special issue must adhere to the Style Guidelines of the Computational Linguistics Journal (http://cljournal.org/style.html). The submission guidelines can be found in the Computational Linguistics web site (http://cljournal.org/submissions.html). As in regular submissions to the journal, paper submissions should be made through the CL electronic submission system (http://cljournal.org/submissions/index.php/cljournal).

GUEST EDITORS

Roser Morante

CLiPS – University of Antwerp, Belgium
roser.morante(at)ua.ac.be

Caroline Sporleder

Computational Linguistics and Phonetics – Saarland University, Germany
csporled(at)coli.uni-sb.de

Call for papers on Social Signal Processing and Mobile HCI

Mission

Given their status as a preeminent form of social interaction, mobile phone conversations have been the subject of relatively limited investigation, in terms of social behavior. This leaves open a major gap when two important developments take place. On one hand, Mobile HCI often deals with advanced mobile phones containing a large number of sensors (e.g., GPS, accelerometers, magnetometers, capacitive touch) and with sufficient processing power to capture with unprecedented richness behavior and context of users (e.g., position, movement, hand grip, proximity of social network members, gait type, auditory context).

On the other hand, the computing community, in particular Social Signal Processing (SSP), makes significant efforts towards automatic understanding (via analysis of verbal and nonverbal behavior) of social interactions captured with multiple sensors.

This volume aims at bridging the abovementioned gap by gathering contributions from both SSP and Mobile HCI communities. Cross-pollination is expected to extend the investigation area of the two domains and highlight a number of research questions that not only promise to bring significant novelty in both SSP and Mobile HCI, but also require the application of knowledge from both domains to be effectively investigated.

Topics

The research questions to be addressed include, but are not limited to:
– Is it possible to integrate the input of mobile phone sensors in current approaches for automatic analysis of social phenomena in conversations?
– Does context influence the communication behavior of people talking on the phone?
– Does the transmission of nonverbal behavioral cues, so important in face-to-face communication, improve phone conversation experience?
– Does a better understanding of communication behavior influence the design of mobile phones?
– Can we evaluate how use of a mobile phone affects the key social interaction variables of ‘trust’ and ‘competence’ evaluation?.
– Can we create metrics which help us evaluate the effect on social interaction of augmenting the voice channel with other feedback channels?
– Can we create non-vocal, but embodied interaction techniques which are appropriate for mobile use?
– What would be the ethical issues related to the everyday use of in-hand, automated social signal analysis?

Submission information

Deadline: December 15th, 2010

The contributions will be published in a volume of the Springer LNCS series
(http://www.springer.com/computer/lncs?SGWID=0-164-0-0-0)

Formatting instructions are available at the following site:
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0

Papers are expected to be between 6 and 12 pages.

Paper can be submitted at the following URL:
http://www.easychair.org/conferences/?conf=mssp2010

For informal inquiries please contact Alessandro Vinciarelli (vincia(at)dcs.gla.ac.uk)

Post-Doc: University of Southampton

Post-Doc: University of Southampton

A post-doctoral research position on Numerical Methods for Structured Low-rank
Approximation is available from January 2011 in the
Information: Signals, Images, Systems (ISIS) research group of the School of Electronics
and Computer Science (ECS). The position is funded by an ERC starting grant and is
offered initially for three years, with an extension of two more years.

The key objectives of the project are: data approximation by low-complexity models
and model-free data processing. Specific topics of interest are: effective heuristics for
low-rank approximation, robust and efficient local optimisation methods, recursive
identification methods, and application of low-rank approximation in systems and
control, signal and image processing, computer algebra, and machine learning.

We are looking for applicants with strong background in linear algebra and
optimization, having ample experience in numerical software development. Knowledge
in system theory, identification, signal processing, machine leaning, and computer
algebra is an asset.

Informal enquiries regarding the position and applications should be submitted to Ivan
Markovsky (im(at)ecs.soton.ac.uk). The required application documents are:
– CV,
– summary of PhD thesis (1 page),
– statement of current research (1 page), and
– names and addresses of two references.
The closing date for applications is 7th January 2011.

ICML 2011 – Call for Tutorials

The ICML 2011 Organization Committee invites proposals for tutorials to be held at the
28th International Conference on Machine Learning, on Monday, June 28, 2011 in
Bellevue, Washington (http://www.icml-2011.org).

We seek proposals for tutorials on core techniques and areas of knowledge that enjoy
broad interest within the machine learning community. We are interested in tutorials on
established or emerging research topics within the field itself, but we also welcome
tutorials from related research fields or application areas provided that they are of
sufficient interest to the machine learning community. The ideal tutorial should attract a
wide audience. It should be broad enough to provide a gentle introduction to the chosen
research area, but it should also cover the most important contributions in depth.
Proposals that exclusively focus on the presenters’ own work or commercial
presentations are not eligible.

Guidelines for preparing a proposal can be found at:
http://www.icml-2011.org/tutorials.php

Tutorial proposals should be submitted via email in PDF format to tutorials@icml-
2011.org .

The timeline is as follows:

* Tutorial proposals due: January 14, 2011
* Acceptance notification: January 31, 2011
* Website due: March 28, 2011
* Tutorial materials due: June, 6, 2011
* Tutorials date: June 28, 2011

Contact: tutorials@icml-2011.org

Francis Bach and Ulf Brefeld
Tutorial Chairs ICML 2011

Open research positions in Louvain and Brussels

Research positions in Louvain and Brussels, Belgium

Summary
——-
Two 36-months research positions in Pattern Recognition, Data Mining and Statistical Machine Learning are open at (1) the Machine Learning Group, University of Louvain, Louvain-la-Neuve (http://www.ucl.ac.be/mlg), and (2) the IRIDIA Laboratory, University of Brussels (http://code.ulb.ac.be/iridia.home.php), Belgium.

Position description
——————–
Applications are invited for two full-time research positions starting in February 2011 at the (1) Machine Learning Group, Université de Louvain (UCL) and (2) IRIDIA Laboratory, Université Libre de Bruxelles (ULB), Belgium. The researchers will essentially work with Prof. Marco Saerens (to have an idea about the covered research topics, see http://scholar.google.be/scholar?q=m+saerens), Operations & Information Department, Louvain School of Management, Louvain, and Prof. Hugues Bersini, IRIDIA Laboratory, Faculty of Applied Sciences, Brussels (http://code.ulb.ac.be/iridia.home.php). Marco Saerens (marco.saerens(at)uclouvain.be) is the coordinator of the project.

Both vacancies offer a tenure of 36 months. The researchers are expected to carry out research in Computational Linguistics, Pattern Recognition, Data Mining and Machine Learning and to play an active role in an applied research project, which is funding the position. The project, involving four academic partners, focuses on *Text mining* and *Graph mining*. More specifically, the aim is to develop innovative link-analysis and text mining algorithms/models exploiting external onthologies, like wikipedia. The researchers will develop and implement algorithms for extracting knowledge from large graphs or networks and documents. Integration of state-of the-art algorithms and specific novel methods is expected.

The candidates could have the opportunity to start a PhD thesis on the subject if wanted – this is to be discussed.

Location
——–
The Machine Learning Group UCL (MLG, http://www.ucl.ac.be/mlg) is a research group of about 30 researchers that carries out theoretical and applied research on data mining, statistical machine learning, predictive modeling, pattern recognition and computational statistics. The MLG takes part in several applied research projects in domains as diverse as text mining, bioinformatics and biomedical engineering. Collaborations between members of the group are strongly encouraged.

The IRIDIA Laboratory ULB (http://code.ulb.ac.be/iridia.home.php) is a well-renowned artificial intelligence lab of about 40 researchers that carries out theoretical and applied research on swarm intelligence, intelligent robotics, local search, data mining and statistical machine learning. It takes part in several international research projects in different fields of artificial intelligence.

Located in – ULB – and near – UCL – Brussels, both the Université Libre de Bruxelles (http://www.ulb.ac.be) and the Université de Louvain (http://www.uclouvain.be) are known for quality research through their prestigious affiliate research centers and world renowned faculties. They are french-speaking and are located at 25 km from each other. Brussels, the capital of Belgium and of the European Union, is a cosmopolitan city with a very vibrant cultural life spiced up by many international languages. Louvain-la-Neuve is a dynamic university town near Brussels hosting more than 30,000 students.

Qualifications
————–
Applicants for the research positions should be highly interested in areas related to computational linguistics, data mining, pattern recognition, statistical machine learning or computational statistics. In particular, any practical experience on data mining, machine learning, and statistical analysis applied to real problems will be an asset. Applicants are expected to have strong applied mathematics, statistics and programming skills, the ability to work independently, strong interpersonal skills, good english writing and oral communication. Upon offer of a position in MLG-UCL or IRIDIA-ULB, the candidates who are non-EU citizens are required to obtain an appropriate long-term Schengen visa; further information is available from their nearest Belgian embassy.

Deadlines and contacts
———————-
Applicants are encouraged to apply as soon as possible as positions will remain open until filled by a suitable candidate. Deadline is December 26, 2010.

Candidates are invited to send their detailed CV and a cover letter, a copy of their grades and the names/email of two references in .pdf format, by email to marco.saerens(at)uclouvain.be. The subject field of the email must be MLG-JOB.

ULB is an equal opportunity employer and is committed to employing more handicapped individuals and especially encourages them to apply. ULB wishes to increase the proportion of women in areas in which they are underrepresented. Women are strongly encouraged to apply.

Application deadline: December 26, 2010
Contact Adress: Marco SAERENS
Contact Email: marco.saerens(at)uclouvain.be
Posted on 2010-11-19

Lectureships in Statistics, Cambridge

University Lectureships in Statistics (2 posts)
Cambridge, UK

Applications are invited for two University Lectureships in Statistics, to
be held in the Statistical Laboratory, and filled by 1 September 2011 or
by negotiation.

Applicants should be able to demonstrate an outstanding research record.
While there are no formal restrictions as to research area, it is
envisaged that the appointee will develop novel core statistical
methodology, either generic or aimed at specific application areas:
current and planned partnerships include biostatistics, machine learning,
signal processing, physics, economics, etc .Applications from those with a
strong statistical background in cognate subjects will be welcomed.

For full details please see

http://www.statslab.cam.ac.uk/Vacancies/index.html

ICML 2011 – Call for Workshops

CALL FOR ICML 2011 WORKSHOP PROPOSALS

http://www.icml-2011.org/workshops.php

Proposals are solicited for workshops to be held in conjunction with the International Conference on Machine Learning (ICML) 2011 in Bellevue, Washington, USA. The workshops will be held on Saturday July 2, after the ICML conference sessions on June 29-July 1, 2011. These workshops present an excellent opportunity to address a specific machine learning-related topic of your choice.

Workshop day: Saturday, July 2, 2011, Bellevue, Washington, USA
Workshop proposal deadline: Friday, January 14, 2011
Acceptance notification: Monday, February 4, 2011

Workshops are a great format for active research on new topics. The ideal workshop covers a compelling subject of current or upcoming research, and includes an impressive set of speakers with diverse backgrounds to discuss the subject. Discussion via panels, identification of open problems, or a “discussant” are all great components to include.

Organization

The format, style, and content of accepted workshops is under the control of the workshop organizers and largely autonomous from the main conferences. The workshops can be up to seven hours long, split into morning and afternoon sessions. Workshop organizers are expected to manage the workshop content, specify the workshop format, be present to moderate the discussion and panels, invite experts in the domain, and maintain a website for the workshop. Workshop registration will be handled centrally by the main conference.

Submission Instructions

Proposals should clearly specify the following:

– Workshop title (what is it called?)
– Topic (what is it about?)
– Motivation (why a workshop on this topic?)
– Impact and expected outcomes (what will having the workshop do?)
– Potential list of invited speakers (who might come?)
– List of related publications (where can we learn more?)
– Main workshop organizer (who is making it happen?)
– Other organizers (who else is making it happen?)
– Bio for each organizer (who are you?)
– Workshop URL (where will interested parties get more information?)

Detailed descriptions of last year’s workshops can be found at:
http://www.icml2010.org/program.html#workshops

This information should be sent by email (in plain text or pdf format) to workshops(at)icml-2011.org by January 14, 2011.

Postdoctoral Position in Approximate Bayesian Inference / Advanced Image Processing

EPFL’s newly established Probabilistic Machine Learning Lab
(http://upseeger.epfl.ch/) has an opening for a post-doctoral fellow in the
field of Bayesian machine learning / computer vision. The initial appointment
is for 12 months, extensions up to 3 years are possible. Topics of interest
are:

– Variational approximate Bayesian inference, particularly in large scale
generalized linear model settings
– Structured image modelling. Inference over sequences (stacks) of image
frames, with particular emphasis on parallel computing (applications in
medical imaging, computer vision, and elsewhere)
– Applications to adaptive compressive sensing, medical imaging, and low-level
computer vision, among others
– Theoretical analysis of variational inference approximations and Bayesian
adaptive compressive sensing

Position:

The Probabilistic ML laboratory offers the chance for seminal work to
establish approximate Bayesian computations in domains not previously
attempted. It is set within Europe’s highest ranked computer and communication
sciences faculty at EPFL, one of the leading technical universities worldwide,
with ample opportunities for collaborations at highest international rank.

EPFL is located next to Lake Geneva in a beautiful setting 60 kilometers
away from the city of Geneva. Salaries are internationally competitive.

Education:

Applicants are expected to have finished, or be about to finish their
Ph.D. degrees. They must have an exceptional background in probabilistic
machine learning, and a firm grasp of approximate Bayesian machine learning
and/or advanced (medical) image processing. A strong track record of
publications at top ML or CV conferences (NIPS, ICML, UAI, JMLR, CVPR, ICCV,
PAMI, IJCV) and/or top-ranked (medical) image processing journals is essential.
Further pluses are strong scientific programming skills (C++, Matlab), prior
exposure to (medical) image/signal processing practice.
The working language at EPFL is English (decent skills essential), French is
not required.

Application:

Please send your applications by email to
Prof. Matthias Seeger (matthias.seeger(at)epfl.ch)
Make sure to include:
– Statement of interest
– Curriculum vitae
– List of publications (add copies of 2-3 strongest papers in the area of
interest of this call)
– Contact details for three references

The deadline for applications is

January 15, 2011

Candidates who happen to attend the forthcoming Neural Information Processing
Systems conference (Vancouver, December 2010), should make themselves known
to Matthais Seeger there.

COLT 2011 Call for Papers

The 24rd Annual Conference on Learning Theory (COLT 2011) will take
place in Budapest, Hungary, on July 9-11, 2011. It will be co-located
with the Foundations of Computational Mathematics conference (FOCM
2011, Budapest, July 4th – 14th, 2011).

http://colt2011.sztaki.hu/

We invite submissions of papers addressing theoretical aspects of
machine learning and empirical inference. We strongly support a broad
definition of learning theory, including:
* Analysis of learning algorithms and their generalization ability
* Computational complexity of learning
* Bayesian analysis
* Statistical mechanics of learning systems
* Optimization procedures for learning
* Kernel methods
* Boolean function learning
* Unsupervised and semi-supervised learning and clustering
* On-line learning and relative loss bounds
* Planning and control, including reinforcement learning
* Learning in social, economic, and game-theoretic settings
* Analysis of learning in related fields: natural language processing,
neuroscience, bioinformatics, privacy and security, machine vision,
data mining, information retrieval

We are also interested in papers that include viewpoints that are new
to the COLT community. We welcome experimental and algorithmic papers
provided they are relevant to the focus of the conference by
elucidating theoretical results. Also, while the primary focus of the
conference is theoretical, papers can be strengthened by the inclusion
of relevant experimental results.

Papers that have previously appeared in journals or at other
conferences, or that are being submitted to other conferences, are not
appropriate for COLT. Papers that include work that has already been
submitted for journal publication may be submitted to COLT, as long as
the papers have not been accepted for publication by the COLT
submission deadline (conditionally or otherwise) and that the paper is
not expected to be published before the COLT conference (June 2010).

Papers will be published electronically without printed proceedings.

Paper awards:
COLT will award both the best paper and best student paper. Best
student papers must be authored or coauthored by a student. Authors
must indicate at submission time if they wish their paper to be
eligible for a student award. This does not preclude the paper to be
eligible for the best paper award.

Open Problems Session:
We also invite submission of open problems (see separate call). These
should be constrained to two pages. There is a shorter reviewing
period for the open problems. Accepted contributions will be allocated
short presentation slots in a special open problems session and will
be allowed two pages each in the proceedings.

Submission Instructions:
Formatting and submission instructions will be available at the
conference website.

Important Dates:
Paper submission deadline: February 11, 2011
Author notification: May 2, 2011
Conference: Jul 9 – 11, 2011

Program Chairs:
Sham Kakade and Ulrike von Luxburg

ESANN 2011: last CFP and special sessions

ESANN 2011

19th European Symposium on Artificial Neural Networks, Computational Intelligence
and Machine Learning Bruges (Belgium) – April 27-28-29, 2011
http://www.dice.ucl.ac.be/esann

Last call for papers and special sessions
======================================================

Deadline for submission of papers:
———————————-
24 November 2010

Topics
——
Machine learning, artificial neural networks, computational intelligence and related
topics (see below for a more detailed description of the conference topics).

Special sessions
—————-
(see http://www.dice.ucl.ac.be/esann for abstracts):
1) Learning of causal relations
Michael Biehl (Univ. of Groningen), Tom Heskes (Radboud Univ. Nijmegen, The
Netherlands), Joris Mooij (MPI for Biological Cybernetics, Tübingen, Germany), John
Quinn (Makerere Univ., Kampala, Uganda)
2) Seeing is believing: The importance of visualization in real-world machine learning
applications Alfredo Vellido (Technical Univ. of Catalonia, Spain), José D. Martín
(Univ.
of Valencia, Spain), Paulo J. G. Lisboa (Liverpool John Moores Univ., UK), Fabrice
Rossi (Télécom ParisTech, France)
3) Deep Learning
Hélène Paugam-Moisy (Univ. de Lyon), Sébastien Rebecchi, Sylvain Chevallier (INRIA
Saclay), Ludovic Arnold (Univ. Paris-Sud 11, France)
4) Computational Intelligence in Life Sciences Frank-Michael Schleif (Univ. of
Bielefeld), Udo Seiffert (Fraunhofer IFF & Univ. of Magdeburg), Dietlind Zühlke
(Fraunhofer FIT, St. Augustin, Germany)
5) Kernel Methods for Structured Data
Giovanni Da San Martino, Alessandro Sperduti (Univ. of Padua, Italy)
6) Information theory related learning
Thomas Villmann (Univ. of Apllied Sciences Mittweida, Germany), Andrzej Cichocki
(Riken, Japan), Jose Principe (Univ. of Florida, USA)

Scope and topics
—————-
Since its first happening in 1993, ESANN has become a reference for researchers on
fundamentals and theoretical aspects of artificial neural networks, computational
intelligence, machine learning and related topics.
Each year, around 100 specialists attend ESANN, in order to present their latest results
and comprehensive surveys, and to discuss the future developments in this field.

The ESANN’2011 conference will follow this tradition, while adapting its scope to the
new developments in the field. The ESANN conferences cover artificial neural
networks, machine learning, statistical information processing and computational
intelligence. Mathematical foundations, algorithms and tools, and applications are
covered.

The following is a non-exhaustive list of machine learning, computational intelligence
and artificial neural networks topics covered during the ESANN
conferences:

THEORY and MODELS
Statistical and mathematical aspects of learning Feedforward models Kernel machines
Graphical models, EM and Bayesian learning Vector quantization and self-organizing
maps Recurrent networks and dynamical systems Blind signal processing Ensemble
learning Nonlinear projection and data visualization Fuzzy neural networks
Evolutionary computation Bio-inspired systems

INFORMATION PROCESSING and APPLICATIONS
Data mining
Signal processing and modeling
Approximation and identification
Classification and clustering
Feature extraction and dimension reduction Time series forecasting Multimodal
interfaces and multichannel processing Adaptive control Vision and sensory systems
Biometry Bioinformatics Brain-computer interfaces Neuroinformatics

Papers will be presented orally (single track) and in poster sessions; all posters will be
complemented by a short oral presentation during a plenary session. It is important to
mention that the topics of a paper decide if it better fits into an oral or a poster session,
not its quality. The selection of posters will be identical to oral presentations, and both
will be printed in the same way in the proceedings. Nevertheless, authors must indicate
their preference for oral or poster presentation when submitting their paper.

Location
——–

The conference will be held in Bruges (also called “Venice of the North”), one of the
most beautiful medieval towns in Europe. Bruges can be reached by train from
Brussels in less than one hour (frequent trains). The town of Bruges is world-wide
known, and famous for its architectural style, its canals, and its pleasant atmosphere.

The conference will be organized in a hotel located near the centre (walking
distance) of the town. There is no obligation for the participants to stay in this hotel.
Hotels of all levels of comfort and price are available in Bruges; there is a possibility to
book a room in the hotel of the conference at a preferential rate through the conference
secretariat. A list of other smaller hotels is also available.

The conference will be held at the Novotel hotel, Katelijnestraat 65B, 8000 Brugge,
Belgium.

Proceedings and journal special issue
————————————-
The proceedings will include all communications presented to the conference (tutorials,
oral and posters), and will be available on-site. Extended versions of selected papers
will be published in the Neurocomputing journal (Elsevier).

Call for contributions
———————-

Prospective authors are invited to submit their contributions before November 24, 2010.
The electronic submission procedure is described on the ESANN portal
http://www.dice.ucl.ac.be/esann/.

Authors must also commit themselves that they will register to the conference and
present the paper in case of acceptation of their submission (one paper per registrant).
Authors of accepted papers will have to register before February 28, 2011; they will
benefit from the advance registration fee. The ESANN conference applies a strict
policy about the presentation of accepted papers during the conference: authors of
accepted papers who do not show up at the conference will be blacklisted for future
ESANN conferences, and the lists will be communicated to other conference organizers.

Deadlines
———
Submission of papers 24 November 2010
Notification of acceptance 18 January 2011
ESANN conference 27-29 April 2011

Conference secretariat
———————-
ESANN’2011
d-side conference services phone: + 32 2 730 06 11
24 av. L. Mommaerts Fax: + 32 2 730 06 00
B – 1140 Evere (Belgium) E-mail: esann(at)dice.ucl.ac.be
http://www.dice.ucl.ac.be/esann

Steering and local committee (to be confirmed)
—————————-
François Blayo Ipseite (CH)
Gianluca Bontempi Univ. Libre Bruxelles (B)
Marie Cottrell Univ. Paris I (F)
Jeanny Hérault INPG Grenoble (F)
Mia Loccufier Univ. Gent (B)
Bernard Manderick Vrije Univ. Brussel (B)
Jean-Pierre Peters FUNDP Namur (B)
Joos Vandewalle KUL Leuven (B)
Michel Verleysen UCL Louvain-la-Neuve (B)
Louis Wehenkel Univ. Liège (B)

Scientific committee (to be confirmed)
——————–

Fabio Aiolli Univ. degli Studi di Padov (I)
Cecilio Angulo Univ. Polit. de Catalunya (E)
Miguel Atencia Univ. Malaga (E)
Michael Biehl University of Groningen (NL)
Martin Bogdan Univ. Tübingen (D)
Hervé Bourlard IDIAP Martigny (CH)
Antonio Braga Federal Univ. of Minas Gerais (Brazil)
Joan Cabestany Univ. Polit. de Catalunya (E)
Stéphane Canu Inst. Nat. Sciences App. (F)
Valentina Colla Scuola Sup. Sant’Anna Pisa (I)
Nigel Crook Oxford University (UK)
Holk Cruse Universität Bielefeld (D)
Tijl De Bie University of Bristol (UK)
Massimo De Gregorio Istituto di Cibernetica-CNR (I)
Dante Del Corso Politecnico di Torino (I)
Wlodek Duch Nicholas Copernicus Univ. (PL)
Marc Duranton NXP Semiconductors (USA)
Richard Duro Univ. Coruna (E)
Deniz Erdogmus Oregon Health & Science University (USA)
Anibal Figueiras-Vidal Univ. Carlos III Madrid (E)
Jean-Claude Fort Université Paul Sabatier Toulouse (F)
Felipe M. G. França Universidade Federal do Rio de Janeiro (Brazil)
Leonardo Franco Univ. Malaga (E)
Damien François Université catholique de Louvain (B)
Colin Fyfe Univ. Paisley (UK)
Marco Gori Univ. Siena (I)
Bernard Gosselin Fac. Polytech. Mons (B)
Manuel Grana UPV San Sebastian (E)
Anne Guérin-Dugué IMAG Grenoble (F)
Barbara Hammer Clausthal Univ. of Technology (D)
Martin Hasler EPFL Lausanne (CH)
Verena Heidrich-Meisner Ruhr-Univ. Bochum (D)
Tom Heskes Univ. Nijmegen (NL)
Katerina Hlavackova-Schindler Austrian Acad. of Sciences (A)
Christian Igel Ruhr-Univ. Bochum (D)
Jose Jerez Univ. Malaga (E)
Gonzalo Joya Univ. Malaga (E)
Christian Jutten INPG Grenoble (F)
Juha Karhunen Helsinki Univ. of Technology (FIN)
Stefanos Kollias National Tech. Univ. Athens (GR)
Jouko Lampinen Helsinki Univ. of Tech. (FIN)
Petr Lansky Acad. of Science of the Czech Rep. (CZ)
Beatrice Lazzerini Univ. Pisa (I)
Amaury Lendasse Aalto University (FIN)
John Lee Univ. Cat Louvain (B)
Priscila M. V. Lima Universidade Federal do Rio de Janeiro (Brazil)
Paulo Lisboa Liverpool John Moores University (UK)
Erzsebet Merenyi Rice Univ. (USA)
David Meunier University of Cambridge (UK)
Anke Meyer-Bäse Florida State university (USA)
Jean-Pierre Nadal Ecole Normale Supérieure Paris (F)
Yoan Miche Aalto University (FIN)
Erkki Oja Aalto University (FIN)
Tjeerd olde Scheper Oxford Brookes University (UK)
Georges Otte Dr. Guislain Institute (B)
Gilles Pagès Univ. Paris 6 (F)
Hélène Paugam-Moisy Université Lumière Lyon 2 (F)
Kristiaan Pelckmans K. U. Leuven (B)
Gadi Pinkas The Center for Academic Studies (Israel)
Alberto Prieto Universitad de Granada (E)
Didier Puzenat Univ. Antilles-Guyane (F)
Leonardo Reyneri Politecnico di Torino (I)
Jean-Pierre Rospars INRA Versailles (F)
Fabrice Rossi Telecom ParisTech (F)
David Saad Aston Univ. (UK)
Francisco Sandoval Univ.Malaga (E)
Jose Santos Reyes Univ. Coruna (E)
Craig Saunders Xerox Research Centre Europe (F)
Frank-Michael Schleif Univ. Leipzig (Germany)
Benjamin Schrauwen Univ. Gent (B)
Udo Seiffert Fraunhofer-Institute IFF Magdeburg (D)
Bernard Sendhoff Honda Research Institute Europe (D)
Alessandro Sperduti Università degli Studi di Padova (I)
Jochen Steil Univ. Bielefeld (D)
John Stonham Brunel University (UK)
Johan Suykens K. U. Leuven (B)
John Taylor King’s College London (UK)
Peter Tino University of Birmingham (UK)
Claude Touzet Univ. Provence (F)
Thiago Turchetti Maia Fed.Univ.Minas Gerais (Brazil)
Marc Van Hulle KUL Leuven (B)
Alfredo Vellido Polytechnic University of Catalonia (E)
Pablo Verdes Novartis Phrama (CH)
David Verstraeten Univ. Gent (B)
Thomas Villmann Univ. Apllied Sciences Mittweida (D)
Heiko Wersing Honda Research Institute Europe (D)
Axel Wismüller University of Rochester, New York (USA)
Bart Wyns Ghent University (B)