IDA-2009 – Final Call for Papers

IDA 2009: The eighth International Symposium on Intelligent Data Analysis

August 31th, September 2nd – 2009

Call for Papers

Over the past decade, there has been a growing body of literature on the understanding of data analysis processes. Making smart use of the increasingly sophisticated analysis algorithms requires much expert knowledge to be part of the process itself, often in an interactive way. This knowledge is at least partially integrated into more complex data analysis meta-methods and modeling scenarios that have proven beneficial. In addition to more traditional algorithmic or application oriented submissions, IDA-2009 especially encourages submissions of papers addressing this emerging trend at the crossroads of traditional data analysis methods, complex data analysis scenarios and interactive tools that assist the analyst throughout the process. We are interested in papers describing methods that aid the analyst in the analysis procedure and we are also looking for contributions abstracting or formalizing the – often interactive – data analysis process. Contributions describing such methods should highlight potential insights into the data that the presented method offers. Examples of interesting scenarios describing steps from data to interesting models are abstractions or formalizations in terms of, for instance, generic workflows or data analysis “design patterns”. Also, description and support for interactivity in data analysis processes are of particular interest. Methods can stem from, but are not limited to, the areas of Machine Learning, Statistics, Data Mining, Artificial Intelligence, and (Interactive) Visualization.

Proceedings and venue

The maximum length of submitted papers is 12 pages in the Springer Lecture Notes in Computer Science format. The proceedings of IDA 2009 will appear in this prestigious series. Notice that Lyon will host VLDB 2009 (35th International Conference on Very Large Databases) from August 24 to August 28. Lyon is listed as a UNESCO World Heritage Site and we invite you to enjoy its splendor and its wonderful way of life.

Important dates:

Submission due: 30 March 2009
Notification of acceptance: 7 May 2009
Camera-ready copy due: 28 May 2009
Conference: August 31 – Sept 01-02 2009

Topics of interest :

Algorithms & Techniques (Machine Learning, Data Mining, Statistics):

* Artificial neural networks – Bayesian networks – Heuristic methods
* Optimization problems – Case-based reasoning – Computational models of human learning
* Computational learning theory – Cooperative learning – Unsupervised learning
* Decision and induction
* Evolutionary computation
* Grammatical inference
* Incremental and on-line learning
* Information retrieval and learning
* Knowledge acquisition and learning
* Data pre- and post-processing
* Data visualisation
* Statistical pattern recognition and analysis
* Performance and optimization
* Bootstrap and randomization
* Causal modeling
* Decision analysis
* Exploratory data analysis
* Knowledge-based analysis
* Classification, projection, regression, optimization clustering
* Data cleaning
* Model specification, selection, estimation
* Reasoning under uncertainty
* Uncertainty and noise in data

Theoritical contributions (Data analysis principles, Data modeling):

* Data Mining theories
* Information retrieval restrictions
* Legal data analysis restrictions
* Innovative data analysis (models, information types, and objectives)
* Theoretical IDA issues
* New paradigms
* Analysis of IDA algorithms

Applications Fields (Practical, Applied and Industrial Data Analysis):

* Analysis of different kinds of data (e.g., censored, temporal etc.)
* Applications (e.g., commerce, engineering, finance, legal, manufacturing, medicine, public policy, science, bioinformatics, biosurveillance)
* Assistants, intelligent agents for data analysis evaluation of IDA systems
* Human-computer interaction in IDA
* IDA systems and tools
* Information extraction, information retrieval
* Experiment design

Conference officers:

General Chair:
Jean-François Boulicaut (INSA Lyon, F)
Program Chairs:
Niall Adams (Imperial College London, UK) Céline Robardet (INSA Lyon, F)
Arno Siebes (Universiteit Utrecht, NL)
Local Organisation:
Guillaume Beslon (INSA Lyon, F)
Céline Robardet (INSA Lyon, F)
Publicity Chair:
Bruno Crémilleux (University of Caen, F)

2nd call for paper MLSP 2009

The 2009 IEEE International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING (IEEE MLSP’09) will be held in Grenoble, France next August.

You will find all relevant information about the venue, the scope and the submisison procedure on the following website:

Formerly known as the IEEE Workshop on Neural Networks for Signal Processing, this workshop is the 19th of a very successful series of meetings. It aims at gathering all the researchers dealing with Machine
Learning, from the most advanced theoretical concepts to the most diverse applications.

Please note the the expected extended deadline for the submission of the full papers is getting closer: April 15th. For your convenience, the Latex and Word templates are already available on the website.

This year, the workshop will include some very exiting events:
– one tutorial will be given by Prof. Tulay Adali on complex-valued adaptive signal on september 1st
– one special session on “Machine Learning in Remote Sensing Data Processing” organized by Prof. Gustavo Camps Valls- one special session on “Brain-computer interfaces”, organized by José
>Millan and Marco Congedo
– one special session on “Learning in Markov models”, organized by Prof.W. Pieczynski
– one data analysis competition (
– two outstanding pleanry speakers:
Prof. Jeanny Herault, on “Scene variability and perception constancy in the visual system: a model of pre-processing before data analysis and learning”
Prof. Lars Kai Hansen, on “Cognitive components of digital media”

ECML PKDD 2009 Call for papers – Reminder

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

September 7-11, 2009
Bled, Slovenia

Key Dates
Abstract submission deadline: April 3, 2009
Paper Submission deadline: April 14, 2009
Paper Acceptance Notification: June 5, 2009
Paper Camera Ready: June 12, 2009
Call For Papers

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases provides an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. Encouraged are submissions of papers that describe the application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques. Submissions that demonstrate both theoretical and empirical rigor are especially encouraged.

Proceedings and Journal

The conference proceedings will be published by Springer. A selection of papers will be directly published in the special journal issues “Data Mining and Knowledge Discovery” and in “Machine Learning Journal”. All other accepted submissions will be published in the Lecture Notes in Artificial Intelligence Series.


ECML PKDD 2009 will not accept any paper which, at the time of submission, is under review or has already been accepted for publication in a journal or another conference. Authors are also expected not to submit their papers elsewhere during the review period of ECML PKDD 2009.

The papers must be in English and must be formatted according to the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines.
Authors instructions and style files can be downloaded at .
The maximum length of papers is at most 16 pages in this format.
Papers submitted to ECML PKDD 2009 will normally be reviewed by minimum two referees.
There will be no “blind review” process. Student submissions should be clearly indicated on the submission form.


General chair:
Dunja Mladenic, Jozef Stefan Institute, Slovenia Program Chairs:
Wray Buntine, NICTA, Australia and HIIT, Finland
Marko Grobelnik, Jozef Stefan Institute, Slovenia
John Shawe-Taylor, University College London, UK

Workshop Chair: Rayid Ghani, Accenture Technology Labs, USA
Tutorial Chair: Cedric Archambeau, University College London, UK
Best Papers Chair: Aleksander Kolcz, Microsoft Live Labs, USA
Industrial track Chairs: Marko Grobelnik, Jozef Stefan Institute, Slovenia
Natasa Milic-Frayling, Microsoft Research Cambridge, UK
Discovery challenge Chair: Andreas Hotho, University of Kassel, Germany
Demo chair: Alejandro Jaimes Larrarte, Telefonica Research, Spain
Publicity chair: David R. Hardoon, University College London, UK
Video chair: Mitja Jermol, Jozef Stefan Institute, Slovenia
Local chair: Tina Anzic, Jozef Stefan Institute, Slovenia

Area Chairs: Francis Bach, Hendrik Blockeel, Francesco Bonchi, Pavel Brazdil, Toon Calders, Nitesh Chawla, Walter Daelemans, Tijl De Bie, Johannes Fuernkranz, Thomas Gaertner, Joao Gama, Bart Goethals, Eamonn Keogh, Joost Kok, Jure Leskovec, Stan Matwin, Taneli Mielikainen, Dunja Mladenic, Claire Nedellec, Martin Scholz, David Silver, Bernhard Pfahringer, Steffen Staab, Gerd Stumme, Luis Torgo, Michael Witbrock, Stefan Wrobel.

Lectureships in Statistical Inference & Multi-Modal Interaction

The Department of Computing Science of the University of Glasgow invites applications for three Lectureships in Statistical Inference, Multi-Modal Interaction, and Formal Methods. The post in Statistical Inference will be of particular interest to candidates with strong track records and interests in Bayesian methodology and Statistical Machine Learning.

[A Lectureship is roughly equivalent to a US Assistant Professor]

University of Glasgow
Faculty of Information and Mathematical Sciences Department of Computing Science
3 Lecturer Posts
Salary: £31,513-£35,469 (grade 7)/£38,757 – £44,930 (grade 8)

Computing Science at Glasgow was rated as one of the top 10 departments for research in the UK in the 2008 Research Assessment Exercise. For further information about the Department’s research strengths see and for more information about SICSA see The Scottish Informatics and Computer Science Alliance (SICSA) aims to create a world-leading Computer Science research community across the universities in Scotland. As part of this initiative, the Department of Computing Science is seeking to appoint three lecturers to undertake research and to develop and teach undergraduate or postgraduate courses within the following areas:

Inference, covering statistical inferential methodology, computational statistics and statistical machine learning. We would welcome applicants working in the area of Bayesian Inference, especially those whose research focus is on probabilistic modelling and inferential methodology applied to themes in Multimodal Interaction and Modelling & Abstraction.

Ref: 00023-1 Informal enquiries can be directed to Professor Mark Girolami,
email: girolami (a); tel: 0141 330 1623,

Multimodal Interaction, in particular applicants whose research focus is on the application of machine-learning or inference in context evaluation, location-aware, gestural interaction or information retrieval settings of interaction design.

Ref: 00022-2 Informal enquiries can be directed to Professor Stephen Brewster
email: stephen (at); tel: 0141 330 4966

Formal modelling, theory and analysis, in particular applicants working in the areas of theory and practice of formal modelling, automated analysis and reasoning, complex and concurrent systems, model checking or type theory.

Ref: 00021-1 Informal enquiries can be directed to Professor Muffy Calder,
email: muffy (at); tel: 0141 330 4969

The posts are available at either grade 7 or grade 8 depending upon knowledge/qualifications and experience. For an application pack, please see our website at

Applications should be submitted to the Human Resources Department (Recruitment Section), University of Glasgow, G12 8QQ, not later than 17 April 2009.

Internet Mathematics 2009: call for participation

Internet Mathematics 2009
04.03.2009 – 15.05.2009


‘Internet Mathematics’ is a series of contests, started by Yandex. This year’s contest is the third since its launch in 2004/05. Previously, this event was also held in 2006/07. This year, the competition is targeted mainly at students, postgrads, programmers, and young researchers. The purpose of this contest is to create a higher profile for current challenges in information retrieval and to stimulate research in the field of Web data analysis.

The problem to be solved within ‘Internet Mathematics 2009′ is the same for all participants; to obtain a document ranking function based on learning set. Within Internet Mathematics 2009 we distribute real relevance tables that are used for learning ranking formula at Yandex. The tables contain computed and normalized features of query-document pairs as well as relevance judgments made by Yandex assessors. The tables do not contain original queries or URLs of original documents, semantics of the features is not revealed. Data set corresponds to approximately 20,000 queries and 200,000 documents and is divided into learning set and test set.

Participants can submit their solutions at any time during the competition period. Portion of participants’ submissions will be considered for preliminary public evaluation. After the deadline evaluations will be finalized and the best results will be announced. Winner will be awarded with money prizes (eligibility restrictions apply).

Questions or suggestions about the contest are welcome at

ICML 2009 Workshop on Numerical Mathematics in Machine Learning

NUMML 2009 Numerical Mathematics in Machine Learning


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, and therefore the practical scope of ML as a whole.

Background and Objectives

Our workshop aims to address these shortcomings. Ideally, a code of conduct can be established for MLers combining and modifying numerical primitives, a set of essential rules as 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. One running example will be the linear model, or Gaussian Markov random field, a building block behind sparse estimation, Kalman smoothing and filtering, Gaussian process models, state space models, or (multi-layer) perceptrons. Basic tasks in this model require the solution of large linear systems, eigenvector approximations, matrix factorizations and their low-rank updates. In turn, model structure can often be used to drastically speed up, or even precondition, these low-level numerical computations.

Impact and Expected Outcome

We will call the community’s attention to the increasingly critical issue of numerical considerations in algorithm design and implementation. A set of essential rules for how to use and modify numerical software in ML is required, for which we aim to lay the groundwork in this workshop. These efforts should lead to an awareness of the problems, as well as increased focus on efficient and stable ML implementations. We will encourage speakers to point out useful software packages, together with their caveats, asking them to focus on examples of ML interest. Raising awareness about the increasing importance of stability and predictable run-time behaviour of numerical machine learning algorithms and primitives. Establishing a code of conduct for how to best select and modify existing numerical mathematics code for machine learning problems. Learning about developments in current numerical mathematics, a major backbone of most machine learning methods.

Potential Subtopics

* Solving large linear systems o Arise in the linear model/Gaussian MRF (mean computations), nonlinear optimization methods (Newton-Raphson, IRLS, …) o Linear conjugate gradients o Preconditioning, use of model structure
* B- Numerical linear algebra packages relevant to ML o LAPACK, BLAS, GotoBLAS, MKL, UMFPACK, …
* Eigenvector approximation o Arise in the linear model (covariance estimation), spectral clustering and graph Laplacian methods, PCA o Lanczos algorithm and specialized variants
* Exploiting matrix/model structure, fast matrix-vector multiplication o Matrix decompositions/approximations o Multi-pole methods o FFT-based multiplication
* Matrix factorizations, low-rank updates o Arise in the linear model, Gaussian process/kernel methods o Cholesky updates/downdates
* Parallel numerical computation for ML

Single-Neuron Modeling Competition

The Quantitative Single-Neuron Modeling Competition offers a coherent framework to compare neuronal models and fitting methods.

– The INCF Prize (10 000 CHF)
– The FACETS Award (500 CHF)

Important Dates

– Submissions via the website will open June 25, 2009.
– The submission deadline is August 25, 2009.
– The results will be presented at the INCF Congress of Neuroinformatics in Pilsen, September 6-8, 2009.

For details see:

The organizers of the competition
Richard Naud (EPFL)
Thomas Berger (EPFL)
Brice Bathellier (UBern)
Wulfram Gerstner (EPFL)

Call for Papers: Pattern Recognition in Bioinformatics *EXTENDED DEADLINE*

*Please note that the paper submission deadline has been extended to April 14th.*


4th IAPR International Conference in

Pattern Recognition for Bioinformatics (PRIB 2009)

City Hall, Sheffield, United Kingdom

7 – 9 September 2009

The International Association of Pattern Recognition (IAPR) sponsored conference aims to bring together top researchers, practitioners and students from around the world to discuss the applications of pattern recognition methods in the field of bioinformatics to solve problems in the life sciences. Prospective authors are invited to submit papers in the research areas of interest to the workshop. These include:

Bio-sequence analysis
Gene and protein expression analysis
Protein structure and interaction prediction Motifs and signal detection
Metabolic modelling and analysis
Systems and synthetic biology
Pathway and network analysis
Immuno- and chemo-informatics
Evolution and phylogeny
Biological databases, integration and visualisation

Pattern recognition techniques of interest include, but not limited to:
Static, syntactic and structural pattern recognition Data mining, Data based modelling Neural networks, Fuzzy systems Evolutionary computation and swarm intelligence Hidden Markov models, Graphical models

Pierre Baldi (University of California, Irvine)
Alvis Brazma (European Bioinformatics Institute, Cambridge)
Gunnar Raetsch (Max Planck Institute, Germany)

Paper Submission 14 April 2009
Special Sessions Proposal 1 April 2009
Author Notification 15 May 2009
Camera Ready Papers 1 July 2009
Early Bird Registration 15 July 2009

Accepted papers will be published in the Springer series of Lecture Notes in Bioinformatics (LNBI). Enhanced versions of selected special papers will be included in a special issue in the International Journal of Systems Science.

Awards will be presented to Best Student Paper and the Best Conference Paper. A limited number of travel awards are available to non-EU students.

General Chairs: Visakan Kadirkamanathan (UK), Guido Sanguinetti (UK)
General Co-Chairs: Raj Acharya (USA), Madhu Chetty (Australia)
Programme Chairs: Mahesan Niranjan (UK), Mark Girolami (UK), Jagath
Rajapakse (Singapore) Special Sessions Chair: Cesare Furlanello (Italy)
Tutorials Chair: Florence d’Alche-buc (France) Publicity Chair: Elena
Marchiori (Netherlands) Publications Chair: Josselin Noirel (UK) Local
Organisation Chair: Daniel Coca (UK)
Webmaster: Maurizio Fillipone (UK)

For additional information, contact:
PRIB 2009 Secretariat,
Department of Automatic Control & Systems Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, United Kingdom
Tel: +44 114 2225618
Fax: +44 114 2225661
prib2009 (at)

Call for Abstracts and Participation: Multidisciplinary Symposium on Reinforcement Learning

Call for Abstracts and Participation
Multidisciplinary Symposium on Reinforcement Learning
Dates: June 18-19, 2009
Abstract Deadline: April 10, 2009
Location: Montreal, Canada

In the last 25 years, reinforcement learning research has made great strides and had a significant impact within several fields, including artificial intelligence, optimal control, neuroscience, psychology, economics and operations research. These are diverse areas, with different goals and different evaluation criteria. It is
striking that reinforcement learning ideas are playing new roles in all of them. The Multidisciplinary Symposium on Reinforcement Learning (MSRL) is meant to recognize this confluence of fields, to
celebrate the diversity of reinforcement learning research, and to facilitate the exchange of information among reinforcement learning researchers in all these fields.

The symposium will consist of invited plenary lectures, spanning the breadth of reinforcement learning, and an evening poster session. The confirmed invited speakers are:

-Andrew G. Barto, University of Massachusetts, Amherst, USA
-Dimitri Bertsekas, Massachusetts Institute of Technology, USA
-Peter Dayan, University College London, U.K.
-Read Montague, Baylor College of Medicine, USA
-Andrew Ng, Stanford University, USA
-Warren Powell, Princeton University, USA
-Wolfram Schultz, University of Cambridge, U.K.
-Terrence Sejnowski, Salk Institute, USA
-Richard Sutton, University of Alberta, Canada
-Gerald Tesauro, IBM Research, USA
-Benjamin Van Roy, Stanford University, USA

A few other invitations are pending.

The evening poster session is a highlight of the symposium and is a unique opportunity to share your work and network with researchers from the many disciplines that contribute to modern reinforcement learning. For this poster session, MSRL invites abstracts from all areas of reinforcement learning. We are especially interested in work that:

– Highlights the best of RL-related research in any discipline
– Provides general overviews of a research program with an RL component
– Extends RL to new areas or applications
– Tests RL ideas in new ways
– Illustrates the impact of RL in a field

Submissions should consist of an extended abstract of up to 2 pages. Student submissions are particularly encouraged. Please send all submissions to by April 10, 2009.

Notifications of acceptance to the symposium will be sent by May 1, 2009.

MSRL will be co-located in Montreal, Canada, with the International Conference on Machine Learning (ICML), the Conference on Uncertainty in Artificial Intelligence (UAI), and the Conference on Learning Theory (COLT). For more information, please see the MSRL web site at

-MSRL Organizing Committee

Doina Precup, McGill University
Elliot Ludvig, University of Alberta
Richard Sutton, University of Alberta
Shie Mannor, McGill University
Satinder Singh Baveja, University of Michigan

RuSSIR 2009: call for participation

3rd Russian Summer School in Information Retrieval (RuSSIR 2009)
Friday September 11 – Wednesday September 16, 2009
Petrozavodsk, Russia


The 3rd Russian Summer School in Information Retrieval will be held September 11-16, 2009 in Petrozavodsk, Russia. The school is co-organized by the Russian Information Retrieval Evaluation Seminar (ROMIP,, Petrozavodsk State University (, and Institute of Applied Mathematical Research ( Yandex ( confirmed as golden sponsor of the event. The first and second RuSSIRs took place in Ekaterinburg in 2007 and Taganrog in 2008, respectively (see and Both schools were very successful.

Petrozavodsk, the capital of the Republic of Karelia, was founded in 1703. It is a large industrial and cultural center of the Russian North-West. Petrozavodsk is 400 km away from Saint-Petersburg, an overnight train journey from Saint-Petersburg takes about eight hours.

The target audience of the Summer School is advanced graduate and PhD students, post-doctoral researchers, academic and industrial researchers, and developers. The mission of the school is to teach students about a wide range of modern problems and methods in Information Retrieval; to stimulate scientific research in the field of Information Retrieval; and to create an opportunity for informal contacts among scientists, students and industry professionals. RuSSIR2009 will host approximately 100 participants. The working languages of the school are English and Russian.

The main RuSSIR 2009 program includes four courses, five lectures each:

Information Retrieval Modeling
Djoerd Hiemstra, University of Twente

Modeling Web Searcher Behavior and Interactions
Eugene Agichtein, Emory University

Enterprise and Desktop search
Pavel Dmitriev, Yahoo! Labs
Pavel Serdyukov, University of Twente
Sergey Chernov, L3S Research Center

Computational advertising: business models, technologies and issues
James G. Shanahan, Independent Consultant

The Russian Conference for Young Scientists in Information Retrieval will be co-organized with the school. The school is expected to have a versatile social program.

Participation in the school is free of charge. The Program Committee will form the body of participants based on received applications.

RuSSIR 2009 is co-located with the yearly ROMIP meeting ( and Russian Conference on Digital Libraries 2009 (

All inquiries can be sent to school[at]romip[dot]ru.