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KDD-09 Second Call for Research Papers


KDD-2009: The Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09)

Paris, France
June 28 – July 1, 2009.



The annual ACM SIGKDD conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. KDD-09 will feature keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, demonstrations, and the KDD Cup competition.

We invite submissions on all aspects of knowledge discovery and data mining.
We especially encourage papers relevant to KDD that cut across disciplines such as machine learning, pattern recognition, statistics, databases, theory, mathematical optimization, data compression, cryptography, and high performance computing. Papers are expected to describe innovative ideas and solutions that are rigorously evaluated and well-presented. Submissions that describe minor variations of existing methods or only make small or questionable improvements to existing algorithms are discouraged.

Important dates:

***Note the earlier submission deadlines***
Abstract submission: February 2, 2009
Paper submission: February 6, 2009
Notification: April 10, 2009
Conference dates: June 28 – July 1, 2009

Areas of interest include, but are not limited to:

Novel data mining algorithms
Data mining foundations
Innovative applications of data mining
Data mining and KDD systems and frameworks Mining data streams and sensor data Mining multi-media data Mining social networks and graph data Mining spatial and temporal data Mining biological and biomedical data Mining text, Web, semantic web and semi-structured data Mining dynamic data Pre-processing and post-processing in data mining Robust and scalable statistical methods Security, privacy, and adversarial data mining High performance and parallel/distributed data mining Mining tera-/peta-scale data Visual data mining and data visualization Data integration issues in mining Data and knowledge provenance in KDD

All submitted papers will be judged based on their technical merit, rigor, significance, originality, repeatability, relevance, and clarity. Papers submitted to KDD’09 should be original work, not previously published in a peer-reviewed conference or journal. Substantially similar versions of the paper submitted to KDD’09 should not be under review in another peer-reviewed conference or journal during the KDD-09 reviewing period.

Repeatability guideline:

Repeatability is a cornerstone of any scientific endeavor. To ensure the long term viability of the research output of the SIGKDD community, we require open-source/public distribution of the code and the datasets. In those cases where this is not possible due to proprietary considerations, every effort should be made to provide the binary executable. If proprietary datasets are used, every effort should also be made to apply the approach to similar publicly available datasets. Furthermore, the description of experimental results in submitted papers should be accompanied by all relevant implementation details and exact parameter specifications.

Peter Flach and Mohammed J. Zaki
KDD’09 Program Co-Chairs

John Elder and Francoise Soulie Fogelman General Chair

KDD-09 Call for Panel Proposals


The 2009 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09)

June 28 – July 1st, 2009. Paris, France.

The KDD-2009 organizing committee invites proposals for panels to be held at the conference. Panel proposals should address emerging, controversial and critical issues in data mining that would likely to have a lasting impact on the field and would also lead to exciting discussions and debates. A mix of industry, academic and government participants is encouraged.

For this year´s conference we are interested in addressing new topics, particularly centered around human issues related to data mining (e.g., privacy, ethics, cultural differences, applications and implications of data mining on end users, etc.).

Proposal Details:
Panel proposals should be no more than four pages long and should include the following:

– Title of the panel
– The topic and issues to be discussed in the panel
– Name, affiliation, and contact information for the panel organizer
– Names and affiliations of up to four panelists (in addition to the panel
organizer) who have made a commitment to participate
– List of 10 questions that the panel organizer will ask the panelists
– Brief biography of each participant

IMPORTANT: the KDD 09 panels will be summarized in a paper that will be published in the conference proceedings. Therefore, the panel organizer will be requested to collect from the panelists, in writing, the responses to some of the questions well in advance of the conference. The conference panel chair (A. Jaimes) will collect the materials and work with the panel organizers selected to produce the paper. The motivation for having the paper is two-fold: make the panelists´ perspectives available after the conference, and ensure that panelists (and audience) give considerable thought to the issues prior to the panel.

Panel proposals should be sent by e-mail in PDF or ASCII format to the Panel Chair Alejandro Jaimes (ajaimes AT before February 23rd.

KDD’09 Call for Tutorial Proposals



The 2009 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09)

June 28 – Jult 1st, 2009. Paris, France.

KDD’09 will host tutorials covering topics in data mining of interest to the research community as well as application developers. The tutorials will be part of the main conference technical program, and are free of charge to the attendees of the conference.

We invite proposals for half-day tutorials from active researchers and experienced tutors. Ideally, a tutorial will cover the state-of-the-art research, development and applications in a specific data mining direction, and stimulate and facilitate future work. Tutorials on interdisciplinary directions, novel and fast growing directions, and significant applications are highly encouraged. Accepted tutorials will receive one free registration to the conference and an honorarium of $500.

A tutorial proposal should be formatted in the following sections.

1. Title

2. Abstract (up to 150 words)

3. Target audience and prerequisites. Proposals must clearly identify the intended audience for the tutorial (e.g., novice users of statistical techniques, or expert researchers in text mining). What background will be required of the audience? Why is this topic important/interesting to the KDD community? What is the benefit to participants?

4. Outline of the tutorial. Enough material should be included to provide a sense of both the scope of material to be covered and the depth to which it will be covered. The more details that can be provided, the better (up to and including links to the actual slides). Note that the tutors should NOT focus mainly on their own research results. A KDD tutorial is not a forum for promoting one’s research or product.

5. A list of forums and their time and locations if the tutorial or a similar/highly related tutorial has been presented by the same author(s) before, and highlight the similarity/difference between those and the one proposed for KDD’08 (up to 100 words for each entry)

6. A list of tutorials on the same/similar/highly related topics given by other people, and highlight the difference between yours and theirs (up to 100 words for each entry)

7. A list of other tutorials given by the authors, please list the titles, the presenters and the forums only.

8. Tutors’ short bio and their expertise related to the tutorial (up to 200 words per tutor)

9. A list of up to 20 most important references that will be covered in the tutorial

10. (Optional) URLs of the slides/notes of the previous tutorials given by the authors, and any specific audio/video/computerrequirements for the tutorial.

Important dates for the tutorials:

-Proposals due: March 15

-Notification of Acceptance: May 25

Please send your submission to bart.goethals (at)

Tutorials Chair Bart Goethals

Vision and Sports Summer School 2009

Zurich, 17-21 August 2009
application deadline: 10 May 2009


Vision and Sports is a special special kind of summer school. In addition to a broad-range of lectures on state-of-the-art Computer Vision techniques, it offers exciting sport activities, such as Kung-Fu, Ultimate Frisbee, and Volleyball. Sports will be organized by the same internationally renowned experts who deliver the lectures. The school offers the best of both worlds to participants: high-quality teaching on Computer Vision, and lots of fun with a variety of attractive sports. This will offer plenty of opportunity for personal contact between students and teachers.

The Vision and Sports Summer School will cover a broad range of subjects, reflecting the diversity of Computer Vision. Each lecture will cover both basic aspects and state-of-the-art research. Every day there will two Computer Vision classes and one sports session. The classes will include both lectures and practical exercises.

The school is open to about 40 participants, and is targeted mainly to young researchers (Master students and PhD students in particular).


Jiri Matas
Czech Technical University

Marc Pollefeys
ETH Zurich

Carsten Rother
Microsoft Cambridge

Bodo Rosenhahn
University of Hannover

Christoph Lampert
MPI Tuebingen

Bastian Leibe
TU Aachen

Vittorio Ferrari
ETH Zurich


Topics will include:

Local feature extraction
Multi-view geometry
3D reconstruction
Large-scale specific object recognition
Appearance-based object categorization
Shape representation and matching
Contour-based object categorization
Kernel Methods for Computer Vision
Markov Random Fields and Conditional Random Fields for Computer Vision
3D human pose estimation


Tennis, Volleyball, Ultimate Frisbee, Kung-Fu, Unihockey, Table Tennis


The school is open to about 40 participants. Please apply online at

Although priority will be given to young researchers (Master/PhD students in particular), applications from senior researchers and industrial professionals are welcome as well. The registration fee is expected to be around 300 Euro. This fee will include all classes, sports activities, coffee breaks, lunches, and a social dinner. For hotel accommodation, students will get discount rates on hotels affiliated with the Summer School.

Applicants should apply before 10 May 2009.
Notification of acceptance will be sent by 31 May 2009.


PostDoc on road traffic datamining at Mines ParisTech

Applications are invited for a post-doctoral position in road traffic datamining and prediction, for 15 month starting within S1 2009, at Robotics Lab. of Mines ParisTech (Paris, France).

The robotics laboratory (CAOR) of Mines ParisTech, associated with IMARA project of INRIA in LaRA « Joint Research Unit », has been involved in 2 big European projects (REACT and COM2REACT) using V2I (Vehicle toInfrastructure) and V2V (Vehicle To Vehicle) communications for enhancing global « road information system ». In these projects the 2 labs worked in particular on analysis and prediction of traffic for improving preventive re-routing strategies in order to reduce congestions. An algorithm has been developed for reconstructing and predicting traffic from a fleet of « sensor » vehicles regularly sending position/speed/traffic information.
CAOR has just started, again with IMARA, and together with TAO project of INRIA and LET of Lyon, a new collaborative project sponsored by ANR (French national research funding agency). This project will focus on analysis and prediction of road traffic, first on realistic simulated data (to be produced with Metropolis software developed by LET), then on real data.

Research work description
The work to do is firstly data-mining of traffic data, seen as a graph whose each edge is a road section with associated traffic level (mean speed, travel time or congestion level), in order to extract common traffic patterns. For this « pattern mining », the idea is to test various clustering methods, in particular unsupervised training algorithms, such as Kohonen maps and K-means, so as to identify main « attractor » states and/or usual traffic states.
Then, the candidate should try to build a simplified dynamic model, as prediction of transitions between identified patterns. In particular, the possibility to exploit fully the graph structure of roads network shall be examined, by experimenting “graph kernel methods” recently developed and mainly applied in the context of bioinformatics.
A possible extension is analysis of road network as a complex dynamical system (bifurcation diagram, etc…).

The candidate should hold a good PhD in the field of statistical machine-learning and/or data-mining, with:
• Very good knowledge of data mining and analysis techniques, as well as of machine-learning methods;
• Good knowledge in probabilities and statistics (in particular Markovian models);
• Some knowledge on graphs and associated algorithms;
• Good computer programming skills (C/C++/Java)

Speaking French is not absolutely mandatory, but would be a plus.

Duration and date
Duration of post-doctoral contract is 15 month, starting within first semester 2009.

Supervision and contact :
Fabien Moutarde, (+33), Fabien.Moutarde (at)

To apply:
Candidates must send a detailed CV, with a cover letter, main publications (or links), together with name and contact of at least 2 references, to above e-mail address.

The Analysis of Patterns – Call for Participation

You are invited to participate in the third course on:

Pula Science Park (Cagliari)
Pula, Italy
September 27th – October 3rd, 2009

Organizers: Nello Cristianini, Fabio Roli, Tijl de Bie


* Florent Nicart – Université de Rouen
* Jean Philippe Vert – Mines Paris Tech
* John Shawe-Taylor – University College London
* Nello Cristianini – University of Bristol
* Bart Goethals – University of Antwerp
* Elisa Ricci, Idiap
* Fabio Roli, University of Cagliari

+ Research Seminars (to be announced)


Every aspect of modern society has been affected by the data revolution. Cheap collection, storage and transmission of vast amounts of information have revolutionized the practice of science, technology and business. Ideas from various disciplines have been deployed to help in the task
of designing computer systems that can automatically detect and exploit useful regularities (patterns) in general types of data.

This is the third meeting of a series devoted to pursuing a unified theoretical description of the various branches of Pattern Analysis. These include statistical approaches to pattern recognition,
combinatorial approaches to pattern matching, grammatical representations of structures, and many more fields of mathematics and computer science. The summer school will aim to emphasize a fundamental unity in goals and methods in all these diverse fields, to enhance our understanding of the central principles of pattern analysis, and to assist in the development of new pattern analysis approaches.

The meeting is interdisciplinary in nature, and can be seen both as a School for advanced students, and as a Workshop for researchers. Leading researchers in various subfields of pattern analysis will hold tutorials on their subject area, while new ideas will be presented in poster sessions, discussions and short seminars. Students in machine learning, pattern recognition, statistics, optimization, data mining, bioinformatics, are particularly encouraged to apply.

The registration fee for the School is 680 Euro per person for a double room (820 Euro for a single room) and includes 7 nights accommodation, meals and school fees.

Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

Registrations will open in february 2009.

Final Call for ICML/UAI/COLT 2009 Workshop Proposals

Montreal, Canada, June 18 2009
Proposal Deadline: Mon 19 Jan, 2009
Acceptance Notification: February 2, 2009

The ICML, UAI, and COLT conferences will be colocated in Montreal June
14-21 2009. We solict proposals for workshops to be held during a single joint workshop day on June 18. This date lies between ICML (June 14-17) and UAI/COLT (June 19-21). Workshops will be selected on the basis of their interest to the attendees of one or more of the conferences.

The goal of the workshops is to provide an informal forum for researchers to discuss important research questions and challenges. Controversial issues, open problems, and comparisons of competing approaches are encouraged. Representation of alternative viewpoints and panel-style discussions are also encouraged.

* 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 will be seven hours long and split into morning and afternoon sessions. Workshop organizers will be 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 conferences with a single uniform registration fee and with registrants allowed to attend workshops other than the one they register for.

* Submission Instructions

Proposals should specify clearly all of the following:

* the workshop’s 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 invited speakers (who might come?)
* a 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?)
* workshop URL (where will interested parties get more information?)
* relevant conferences (which of ICML, UAI, and COLT would it appeal to?)

Please also provide brief CVs of all organizers.
This information should be sent by email (in plain text or pdf format) to
Icml-uai-colt-workshops09 (at)
by 19 Jan 2009.

Jeff Bilmes and Andrew Ng: UAI co-chairs Sham Kakade: COLT workshops chair Chris Williams: ICML 2009 workshops chair

Call for papers: Journal of Machine Learning Research , Special Topic on Large Scale Learning – Dedline Extension

With the exceptional increase in computing power, storage capacity and network bandwidth of the past decades, ever growing datasets are collected in fields such as bioinformatics (Splice Sites, Gene Boundaries, etc), IT-security (Network traffic) or Text-Classification (Spam vs. Non-Spam), to name but a few. While the data size growth leaves computational methods as the only viable way of dealing with data, it poses new challenges; specifically, most machine learning algorithms hardly scale up beyond 1,000,000 examples or dimensions.

A special topic of the Journal of Machine Learning Research will be devoted to Large Scale Learning, in the line of the NIPS 2007 and ICML 2008 “Efficient Machine Learning” Workshops, and of the Pascal Challenge on Large Scale Learning (

You are invited to submit your contributions to this special issue. For the sake of a principled and fair evaluation, binary classification algorithms must be assessed on the datasets and along the experimental protocol devised for the Large Scale Learning Challenge. More information about the challenge protocol can be found here:

Important dates

Submission: 5 February 2009 ***NEW***
Decision: 15 March 2009
Final versions: 15 April 2009

Topics of Interest

Topics of interest include:

* Applications to very large scale problems in, e.g., bioinformatics, textcategorization, network data
* Efficient training algorithms, e.g., SVMs solvers
* Learning with a budget, e.g., under strict time or memory constraints.
* Efficient parallelization of machine learning algorithms
* Efficient data structures
* On-line learning algorithms
* Large-scale kernel methods
* Coarse to fine algorithms
* Algorithms making use of new hardware, e.g., GPUs, Xilinx

Submission procedure

Authors are kindly invited to follow the standard JMLR format and submission procedure JMLR submission format, the number of pages is limited to 30. Please include a note stating that your submission is for the special topic on Large Scale Learning.

Guest editors

Soeren Sonnenburg, Fraunhofer Institute FIRST, Berlin, Germany
Vojtech Franc, Fraunhofer Institute FIRST, Berlin, Germany
Elad Yom-Tov, IBM Haifa Research Lab, Haifa, Israel
Michele Sebag, LRI, Orsay, France

Fully Funded PhD Studentship in Systems Biology

British Heart Foundation Fully Funded PhD Studentship in Systems Biology


Dr. Tim Palmer (, Integrative and Systems Biology)
Prof. Mark Girolami (,

Regulation of the immune/inflammatory responses by interleukin-6 (IL-6)-family cytokines is dictated by the interplay of multiple cytokine-activated signalling cascades and inhibitory regulators designed to prevent excessive receptor activation that can result in disease. The situation is further complicated by the observation that cytokine-activated signalling cascades are negatively controlled by distinct signalling modules such as those initiated by the prototypical intracellular messenger cyclic AMP. Despite its significance, the extensive level of cross-talk observed has not been integrated into coherent models of IL-6 receptor signalling and its regulation.

By combining molecular/cell biology with mathematical modelling & statistical inferential approaches, this inter-disciplinary studentship will A) statistically define minimal network structures that accurately describe cytokine signalling pathway kinetics, B) derive a set of plausible mathematical models that can identify the critical parameters controlling inhibitory cross-regulation of gp130 by cyclic AMP, and C) identify new approaches for limiting excessive cytokine signalling associated with inflammatory disorders.

The project provides an exciting opportunity for high-quality doctoral training in mathematical modelling & statistical inferential approaches and their application to increase our understanding of the architecture and dynamics of molecular cell signalling pathways. In addition to contemporary
molecular and cellular biology techniques (mammalian cell culture, RNAi-mediated knockdown, protein analysis), the successful candidate will be trained in mathematical modelling of pathway dynamics as well as Bayesian statistical methods to formally characterize uncertainty in these models.

Candidates should be European Economic Area nationals, have an excellent first degree in a relevant mathematical discipline (Mathematics, Computing Science, Statistics, Engineering, Physics) and be highly motivated in their wish to apply this expertise to biological systems. Candidates with an excellent first degree in Biochemistry, Molecular and Cellular Biology or a related discipline, coupled with additional experience in applying mathematical/statistical methods to biological systems, will also be considered.

The studentship will commence as soon as possible after a suitable candidate is identified. The studentship will carry a stipend of £16,853 in year 1 and increasing to £18,580 in year 3. The studentship also covers the student¹s university fees. The studentship is renewable, subject to
satisfactory annual progress, for up to a total of three years.

Applications must consist of a current CV, contact details of at least two academic referees, evidence of degree performance, and a completed application form from

Preliminary email enquiries to Tim Palmer or Mark Girolami are welcomed.

Candidates are encouraged to complete the online application, but also to send their CV and associated documents direct to the Graduate School:

Graduate School of Biomedical and Life Sciences, Bower Building,
University of Glasgow, Glasgow G12 8QQ
Tel: ++44 (0)141-330-5800
Fax: ++44 (0)141-330-6093
E-mail: biograd (a) (please type ³BHF Palmer² in the subject box of

Post doctoral position in Machine Learning 2009

Starting: March 2009
Location: Paris, France

TOPICS: machine learning for structured data, social networks, random graphs, graphical models

The Department Signal and Image Processing (TSI) of Telecom ParisTech (France) is offering a one year post-doctoral position in Machine Learning. The post-doctoral fellow will develop and implement machine learning procedures and statistical techniques for investigating the diffusion of information through small social networks. The context of the study is related to food safety and dietary risks.

Candidates will be recruited at the level of a PhD in Mathematics or Statistics. They will have confirmed skills in mathematical modelling, data analysis, statistical or machine learning methods, mathematical programming (Matlab or R), and will be highly motivated for applications to social sciences.

The candidate will enjoy a challenging and rewarding working environment, within a top leading laboratory in the field of Information and Communication Theory.
Team members: Stéphan Clémençon (Telecom ParisTech – TSI), Fabrice Rossi (Telecom ParisTech – INFRES), Nicolas Vayatis (ENS Cachan – CMLA), Sandrine Blanchemanche (INRA Unité Met@risk), Akos Rona-Tas (UCSD Dept of Sociology).

INSTITUTION: Department of Signal and Image Processing of Institut Telecom – and Laboratory LTCI UMR Telecom ParisTech/CNRS 5141 –

FUNDING: position is funded by a new grant « Futur & Rupture « (Institut Telecom).

NET SALARY: ranging from 2200 to 2700 euros per month depending on past experience

CONTACT: Interested applicants should sent C.V. to Stéphan Clémençon
stephan.clemencon (at)