Workshop: The Statistical Physics of Inference and Control Theory

Workshop: http://www.snn.ru.nl/cyberstat_granada/index.html
The Statistical Physics of Inference and Control Theory
Granade, Spain
September 12-16 2012

SCOPE OF THE WORKSHOP

The topic of the present workshop is stochastic optimal control theory and its relations to machine learning and robotics, statistical mechanics, quantum theory and the theory of large deviations.
For many years, the deterministic control theory has dominated control applications in robotics and autonomous systems, mainly because of computational restrictions. Relatively recently, there have been several approaches to restate the stochastic optimal control computation as an inference problem and to obtain efficient solutions using approximate inference. In these control theories, concepts from classical mechanics and control theory (variational calculus and Hamilton-Jacobi equations) and stochastic processes and large deviations theory (Feynman-Kac formula) are intimately related. This approach provides novel insights for the design of efficient algorithms to efficiently compute optimal stochastic control solutions in robotics.
The Hamilton Jacobi equation also plays a crucial role in the computation of non-equilibrium large deviations. In recent developments, this large deviation theory has provided a rather general framework in which the macrobehavior of non-equilibrium systems can be studied. In addition, there is a connection between these control formulations and Nelsons stochastic mechanics, which aims to provide a particle interpretation of quantum mechanics.
This workshop brings together researchers from control theory, machine learning, physics and mathematics to explore these connections.

The workshop will include longer invited talks, a limited number of shorter contributed talks and plenty of
time for discussions. Contributed talks should be submitted before June 1st, 2012.
SPECIFIC TOPICS INCLUDE:

* Stochastic optimal control theory
* Stochastic processes
* Non-equilibrium large deviations
* Stochastic quantum theories and quantum control
* Applications in robotics

Confirmed Invited Speakers

Ari Arapostathis (Austin, Texas)
Bill Bialek (Princeton)
Roger Brockett (Harvard)
Jean-Charles Delvenne (Louvain)
Karl Friston (UC London)
Francesco Guerra (Rome)
Ramon van Handel (Princeton)
Jorge Kurchan (ENS Paris)
Claudio Landim ( IMPA)
Seth Lloyd (MIT)
Marc Mezard (Orsay)
Sanjoy Mitter (MIT)
Jun Morimoto (ATR, Japan)
Pablo Parrilo (MIT)
Juan Parrondo (Madrid)
Henrik Sandberg (KTH, Sweden)
Devavrat Shah (MIT)
Nikolai Sinitsyn (Los Alamos)
Evangelos Theodorou (Washington)
Naftali Tishby (Jerusalem)
Emanuel Todorov (Washington)
Organizing Committee

Misha Chertkov (Los Alamos)
Bert Kappen ( Nijmegen)
Frank Redig (Delft)
Riccardo Zecchina (Torino)
Joaquin Torres (Granada)
Joaquin Marro (Granada)

http://www.snn.ru.nl/cyberstat_granada/index.html

Pascal2-sponsored gesture challenge

Dear colleagues,

Round 2 of the gesture recognition challenge with Kinect sponsored by Pascal2 has started and will last until September 10:
http://gesture.chalearn.org/

You can again
– win 3 prizes offered by Microsoft ($5000, $3000, $2000),
– get travel awards to go in November at ICPR 2012 to present your results in Japan, and
– publish in a special topic of JMLR.

The data are the same as in round 1 (except the final evaluation set), but we provide more annotations and sample code, and an analysis of the results of round 1. See below the high level summary.

Best regards,

Isabelle

ChaLearn takes gesture recognition to the crowd with Microsoft Kinect(TM)

A competition to help improve the accuracy of gesture recognition using Microsoft Kinect(TM) motion sensor technology promises to take man-machine interfaces to a whole new level. From controlling the lights or thermostat in your home to flicking channels on the TV, all it will take is a simple wave of the hand. And the same technology may even make it possible to automatically detect more complex human behaviors, to allow surveillance systems to sound an alarm when someone is acting suspiciously, for example, or to send help whenever a bedridden patient shows signs of distress.

Through its low cost 3D depth-sensing cameras, Microsoft Kinect(TM) has already kick-started this revolution by bringing gesture recognition into the home. Humans can recognize new gestures after seeing just one example (one-shot-learning). With computers though, recognizing even well-defined gestures, such as sign language, is much more challenging and has traditionally required thousands of training examples to teach the software.

To see what the machines are capable of, ChaLearn launched a competition hosted by Kaggle with prizes donated by Microsoft, in the hope they can give the state of the art a rapid boost. The ChaLearn team has been organizing competitions since 2003, featuring hard problems such as discovering cause-effect relationships in data. It has selected the young and dynamic startup Kaggle to host the gesture challenge because Kaggle has very rapidly established a track record for using crowdsourcing to find solutions that outperform state-of-the-art algorithms and predictive models in a wide variety of domains (from helping NASA build algorithms to map dark matter to helping insurance companies improves claims prediction). And now the first round of the gesture challenge helped narrow down the gap between machine and human performance. Over a period of four months starting in December 2011, 153 contestants making 573 entries have built software systems that are capable of learning from a single training example of a hand gesture (so-called one-shot-learning). They lowered the error rate, starting from a baseline method making more than 50% error to less than 10% error.

The winner of the challenge, Alfonso Nieto Castanon, used a method he invented, which is inspired by the human vision system. He and the second and third place winners will be awarded $5000, $3000 and $2000 respectively and get an opportunity to present their results in front of an audience of experts at the CVPR 2012 conference in Rhode Island, USA, in June. A demonstration competition of gesture recognition systems using Kinect(TM) will also be held in conjunction with this event, with similar prizes donated by Microsoft.

Now, from May 7 and until September 10, new competitors can enter round 2 of the challenge and get a chance to close the gap with human performance, which is under 2% error! The entrants are given a set of examples with which to apply and test their algorithms, so that they may improve them. Compared to round 1, they will benefit from a wealth of resources including the fact sheets and published papers of the participants of round 1, data annotations, and data transformations having had success in round 1. During a four month period they will be able to compare their system with those of other contestants, by using it to predict gestures from a feedback sample. Throughout the competition the evaluations of these are posted on a live leaderboard, so participants can monitor their performance in real time. The contestants will then have the opportunity to put their best algorithms to the final test in an evaluation phase. Here they will be given a few days to train their system on an entirely new set of gestures, after which the one with the best recognition score will be rewarded with $5000. Those coming second and third place will receive $3000 and $2000 respectively. Similarly as in round 1, the results will be discussed at a scientific conference (ICPR 2012, Tsukuba, Japan, November 2012) where a demonstration competition will be held also crowned with prizes in the same amount. Microsoft will be evaluating successful participants in all challenge rounds for two potential IP agreements of $100,000 each. See official challenge rules for more details at http://gesture.chalearn.org.

The winner of the first round believes that it is possible to reach and even beat human performance. Others will also join in the race. According to Kaggle, that is the power of the crowd: bringing together expert talent, sometimes from previously untapped quarters. And with Microsoft interested in buying the intellectual property, the hope is that the new algorithms that emerge from the contest will not only boost accuracy but also open the doors to a whole new range of applications. From using communicating with Kinect(TM) through sign language or even speaking, with the algorithms interpreting what you say by reading your lips to smart homes or using gestures to control surgical robots.

The challenge was initiated by the US Defense Advanced Research Projects Agency (DARPA) Deep Learning Program and is supported by the US National Science Foundation, the European Pascal2 network of excellence, Microsoft and Texas Instruments. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors and funding agencies.

ICML 2012 workshop: RKHS and Kernel-based methods

ICML 2012 workshop: RKHS and Kernel-based methods: Theoretical topics
and recent advances

Submissions are invited for the workshop to be held on July 1st at
this years’ ICML workshops in Edinburgh.

Overview:
*********

Research on reproducing kernel Hilbert spaces and kernel-based methods
has witnessed a major impetus during the last two decades. Recent
advances include kernels on structured data, powerful learning
guarantees for kernel-based methods, and Hilbert-space embeddings of
distributions. Moreover, some of the most lively NIPS and ICML
workshops in recent years have dealt with applications where kernel
approaches are popular, most notably multiple kernel learning,
transfer learning, and multitask learning. While kernel-based methods
are well established in the machine learning practice, certain results
in the underlying theory of RKHS remain relatively inaccessible to the
ML community. Moreover, powerful tools for RKHS developed in other
branches of mathematics, for instance in numerical analysis and
probability, are less well known to machine learning researchers.

The proposed workshop represents an opportunity to bring together
researchers in probability theory, mathematicians, and machine
learning researchers working on RKHS methods. The goals of the
workshop are threefold: first, to provide an accessible review and
synthesis of classical results in RKHS theory from the point of view
of functional analysis, probability theory, and numerical analysis.
Second, to cover recent advances in RKHS theory relevant to machine
learners (for instance, operator valued RKHS, kernels on time series,
kernel embeddings of conditional probabilities). Third, to provide a
forum for open problems, to elucidate misconceptions that sometimes
occur in the literature, and to discuss technical challenges.

Confirmed speakers:
*******************

Paul Eggermont, University of Delaware
Saburou Saitoh, Gunma University
Robert Schaback, Georg-August-Universitaet Goettingen
Marco Cuturi, University of Kyoto
Lorenzo Rosasco, MIT

Submission scope:
*****************

Submissions are invited on new research directions in kernel theory,
and on open questions/striking counterexamples illustrating
non-obvious RKHS properties. We expect the latter to provide a
valuable knowledge base for the ML community in general, of
information known informally to practitioners but not easy to find in
journals articles and conference proceedings.

Accepted submissions will be presented in one of three formats.
Long-form reseach will be presented either as a talk or a poster.

Topics suited to spotlight presentation, such as open questions, interesting
examples, or counterexamples, will be presented during discussion
periods set aside for this purpose.

Long-form submissions accepted as posters will also be considered for
spotlight presentation.

The deadline for submission will be May 20th for the poster and talk
presentations. Notification of acceptance will be provided on June 2.
In addition, proposals for spotlight presentation only will be
accepted until June 15th, with notification on June 17th.

Submissions should be no more than TWO pages in a sane font, and
should be sent to bharath@gatsby.ucl.ac.uk with subject “icml12
workshop submission”.

Current workshop information may be found at:

https://sites.google.com/site/icml12kernels

Further information will be posted on the website.

Your Workshop Organizers,

Arthur Gretton
Zaid Harchaoui
Bharath Sriperumbudur

CLEFeHealth2012 and Louhi2013 Workshops: call for short papers (by May 31) and papers (by Oct 15)

Dear Colleagues,

CLEFeHealth 2012 (http://nicta.com.au/business/health/events/clefehealth2012) is the CLEF2012 workshop on cross-language evaluation of methods, applications, and resources for eHealth document analysis with a focus on written and spoken natural-language processing. NICTA, National ICT Australia organises it in Rome, Italy on 17-20 September 2012. Remember to check the other CLEF workshops/labs too, in particular Image CLEF on medical image processing: http://clef2012.org/

Louhi2013 (http://www.nicta.com.au/business/health/events/louhi2013) is the 4th International Workshop on Health Document Text Mining and Information Analysis. Inspired by CLEF2012 and linked with CLEFeHealth2012, the focus of this fourth Louhi workshop is on syntactic, semantic, and pragmatic analysis of health documents; mono- and multilingual methods, applications, and resources for their automated processing and intelligent re-use; cross-language evaluation health documentation and their processing methods, applications, and resources; and methods, resources, and infrastructure for this cross-language evaluation. NICTA organises the workshop in Sydney, NSW, Australia on 11-12 February 2013 in collaboration with the Australian Health Informatics Summer School (Sydney, NSW, Australia; 4-8 February 2013).

Note that the workshops are connected; we encourage submitting first an extended abstract to CLEFeHealth2012 and then a paper to Louhi2013. CLEFeHealth2012 provides mentoring for students who wish to follow this guideline.

Please find more information about the workshops from the attached flyers and distribute the message among your colleagues.

Best Regards,

Hanna Suominen

Researcher, PhD
NICTA, Canberra Research Laboratory

Postal address: Locked Bag 8001, Canberra ACT 2601, Australia
Office address: Room L2-38, Tower A, 7 London Circuit, Canberra City ACT 2601, Australia
Office phone: +61 (0)2 6267 6351
Mobile phone: +61 (0)431 913 826
Web page: http://www.nicta.com.au/people/hanna_suominen

MLSB/OUP Bioinformatics Call for Papers on “Computational Systems Biology”

Call for Papers: Issue on “Computational Systems Biology” in OUP Bioinformatics
in conjunction with
the Machine Learning in Systems Biology Workshop (MLSB 2012) in
Basel, Switzerland, September 8 and 9, 2012
http://mlsb.cc/cfp

MLSB and the Virtual Issue on “Computational Systems Biology”
MLSB12, the Sixth International Workshop on Machine Learning in Systems Biology will be held in Basel, Switzerland on September 8 and 9, 2012. The Workshop is organized as “Satellite Meeting” of the 11th European Conference on Computational Biology (ECCB). The aim of this workshop is to contribute to the cross-fertilization between the research in machine learning methods and their applications to systems biology.
As a new feature of this year’s MLSB, full paper submissions to MLSB will be considered for publication in a virtual issue on “Computational Systems Biology” in a special proceedings section of OUP Bioinformatics. In parallel, we allow submissions of extended abstracts — as stated in the Call for Contributions — solely for oral/poster presentation at MLSB, without consideration for publication in the issue.

Submissions
We are soliciting high-quality papers on all aspects of computational methods in systems biology. All submissions will go through rigorous peer-review. Accepted papers will be presented by the authors in an oral presentation at MLSB and published in the virtual issue on “Computational Systems Biology” in OUP Bioinformatics. Papers requiring extensive revisions will be considered separately as abstract presentations at MLSB and as regular papers for the Bioinformatics journal.

All manuscripts should be submitted via the Bioinformatics online submission system. Manuscripts must adhere to the formatting instructions for “Original papers” in Bioinformatics. During submission please specify MLSB as one of the keywords, and include a cover letter stating the manuscript should be considered for the MLSB meeting. Deadline for paper submission is May 21st.
Authors of papers that were submitted, but not selected, for the main ECCB 2012 meeting may submit an updated version of their ECCB paper with the full ECCB reviews and a clearly marked response to the reviews for MLSB consideration by June 4th. They will be notified of any decision by June 19th.

We encourage all authors to publish under the OUP open access model. Open access fees apply (details).

Key Dates
> May 21 – Paper submission deadline (23:59 in the time zone of your choice).
> June 4 – Revised ECCB manuscript submission deadline
> June 19 – Paper Acceptance Notification
> June 28 – Submission of final revisions to Bioinformatics
>

Issue Editors
Karsten Borgwardt, Max Planck Institutes and University of Tübingen
Gunnar Rätsch, Memorial Sloan-Kettering Cancer Center, New York

CFP (May 9): Big Data Mining Workshop (BigMine-12) at KDD12

Big Data Mining
1st International Workshop on Big Data, Streams and Heterogeneous
Source Mining: Algorithms, Systems, Programming Models and
Applications (BigMine-12)

Conference Dates: August 12-16, 2012
Workshop Date: Aug 12, 2012
Beijing, China

http://www.big-data-mining.org

Key dates:
Papers due: May 9, 2012
Acceptance notification: May 23, 2012
Workshop Final Paper Due: June 8, 2012
Workshop Proceedings Due: June 15, 2012

Paper submission and reviewing will be handled electronically. Authors
should consult the submission site (http://
http://big-data-mining.org/submission/) for full details regarding
paper preparation and submission guidelines.

Papers submitted to BigMine-12 should be original work and
substantively different from papers that have been previously
published or are under review in a journal or another
conference/workshop.

Following KDD main conference tradition, reviews are not double-blind,
and author names and affiliations should be listed.

We invite submission of papers describing innovative research on all
aspects of big data mining.

Examples of topic of interest include

1. Scalable, Distributed and Parallel Algorithms
2. New Programming Model for Large Data beyond Hadoop/MapReduce,
STORM, streaming languages
3. Mining Algorithms of Data in non-traditional formats (unstructured,
semi-structured)
4. Applications: social media, Internet of Things, Smart Grid, Smart
Transportation Systems
5. Streaming Data Processing
6. Heterogeneous Sources and Format Mining
7. Systems Issues related to large datasets: clouds, streaming system,
architecture, and issues beyond cloud and streams.
8. Interfaces to database systems and analytics.
9. Evaluation Technologies
10. Visualization for Big Data
11. Applications: Large scale recommendation systems, social media
systems, social network systems, scientific data mining,
environmental, urban and other large data mining applications.

Papers emphasizing theoretical foundations, algorithms, systems,
applications, language issues, data storage and access, architecture
are particularly encouraged.

We welcome submissions by authors who are new to the data mining
research community.

Submitted papers will be assessed based on their novelty, technical
quality, potential impact, and clarity of writing. For papers that
rely heavily on empirical evaluations, the experimental methods and
results should be clear, well executed, and repeatable. Authors are
strongly encouraged to make data and code publicly available whenever
possible.

Top-quality papers accepted and presented at the workshop after
careful revisions by the authors, reviewed by original PC members and
chairs will be recommended to ACM TIST, ACM TKDD, IEEE Intelligent
Systems or IEEE Computer for fast publication, depending on relevance
of the topic

Vision and sports summer school 2012 – application closes May 15th

_______________________

Application closes May 15th
_________________________

VISION AND SPORTS SUMMER SCHOOL

Prague, 27-31 August 2012

http://cmp.felk.cvut.cz/summerschool2012/
email: vs3@cmp.felk.cvut.cz

application deadline: 15 May 2012

Organized in collaboration with NIFTi
http://www.nifti.eu

OVERVIEW

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
Tennis, Archery, Kung-Fu and Ultimate Freesbee. Sports are 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 offers plenty of opportunity for
personal contact between students and teachers.

The Vision and Sports Summer School covers 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 are
two Computer Vision classes and one sports session. The classes
include both lectures and practical exercises.

The school is open to about 60 participants, and is targeted mainly to
young researchers (Master students and PhD students in particular).

Following the 5-day summer school, there will be a robotic workshop
organized by the EU project NIFTi (www.nifti.eu). The participants
will apply vision algorithms on the NIFTi mobile robot(s) and move the
robot around using the Ladybug3 camera the robot is equipped with.
Attendance to this workshop is optional and limited to a small number
of attendees. http://cmp.felk.cvut.cz/niftivisionworkshop2012/

TEACHERS

Jiri Matas
Czech Technical University

Phil Torr
Oxford Brookes University

Carsten Rother
Microsoft Research Cambridge

Christoph Lampert
IST Austria

Patrick Perez
Technicolor Research and Innovation

Silvio Savarese
University of Michigan

Vittorio Ferrari
University of Edinburgh

Bastian Leibe
RWTH Aachen University

Ondrej Chum
Czech Technical University

COMPUTER VISION LECTURES

Current list of topics:

Local feature extraction
Large-scale specific object recognition
Single-view and multi-view object categorization
MRF/CRF in Computer Vision
Semantic segmentation
Weakly supervised learning of visual models
Kernel Methods in Computer Vision
Tracking in video

SPORT ACTIVITIES

Tennis, Volleyball, Unihockey, Archery, Table Tennis, Soccer, Archery,
Ultimate Freesbee, Kung-Fu, Basketball, Tai chi, Badminton

APPLICATION

The school is open to about 60 participants. Please apply online at

http://cmp.felk.cvut.cz/summerschool2012/

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 for
PhD students is only 300 Euro. This fee includes all classes, sports
activities, coffee breaks, lunches, and a social dinner. For hotel
accommodation, students will get discount rates on hotels affiliated
with the school.

Applicants should apply before 15 May 2012.
Notification of acceptance will be sent by 31 May 2012.

MORE INFORMATION

http://cmp.felk.cvut.cz/summerschool2012/

Deadline extension May 16: Object, functional, structured data ICML 2012 Workshop

2nd CALL FOR CONTRIBUTIONS

Object, functional, structured data : towards next generation kernel-based methods

ICML 2012 Workshop, June 30, 2012, Edinburgh, UK.

https://sites.google.com/site/nextgenkernels/

Important dates

Submission due by May 16, 2012.

Author Notification, May 21, 2012.

Workshop, June 30, 2012.

Topic

This workshop concerns analysis and prediction of complex data such as objects, functions and structures. It aims to discuss various ways to extend machine learning and statistical inference to these data and especially to complex outputs prediction. A special attention will be paid to operator-valued kernels and tools for prediction in infinite dimensional space.

Context and motivation

Complex data occur in many fields such as bioinformatics, information retrieval, speech recognition, image reconstruction, econometrics, biomedical engineering. In this workshop, we will consider two kinds of data: functional data and object or structured data. Functional data refers to data collected under the form of sampled curves or surfaces (longitudinal studies, time series, images). Analysis of these data as samples of random functions rather that a collection of individual observations is called Functional Data Analysis (FDA). FDA involves statistics in infinite-dimensional spaces and is closely associated to operatorial statistics. Its main approaches include functional principal component analysis and functional regression. Many theoretical challenges remain open in FDA and attract an increasing number of researchers.

Object and structure data exhibit an explicit structure like trees, graphs or sequences. For instance, documents, molecules, social networks and again images can be easily encoded as objet structured data. For the two last decades, both machine learning and statistics communities have developed various approaches such as graphical probabilistic models as well as kernel methods to take into account the structure of the data. In the meantime, FDA has been extended to Object Data Analysis which deals with samples of object data.

However, most of the efforts have been concentrated so far on dealing with complex inputs. In this workshop, we would like to emphasize the problem of complex outputs prediction which is involved for instance in multi-task learning, structured classification and regression, and network inference. All these tasks share a common feature: they can be viewed as approximation of vector-valued functions instead of scalar-valued functions and in the most general case, the output space is an Hilbert space. A promising direction first developed in (Micchelli and Pontil, 2005) consists in working with Reproducing Kernel Hilbert Spaces with operator-valued kernels in order to get an appropriate framework for regularization. There is thus a strong link between recent works in machine learning about prediction of multiple or complex outputs and functional and operatorial statistics.

This workshop aims at bringing together researchers from both communities to 1) provide an overview of existing concepts and methods, 2) identify theoretical challenges and (3) discuss practical applications and new tasks.

Invited speakers

Yasemin Altun (Google)

Frédéric Ferraty (University of Toulouse, France)

Arthur Gretton (Gatsby Unit, UCL MPI for Intelligent Systems, UK)

Neil Lawrence (University of Sheffield, UK)

Steve Marron (University of North Carolina, USA)

Charles Micchelli (University of Albany, USA)

Call for contributions

We invite short, high-quality submissions on the following topics:

* complex output learning
* structured output prediction
* functional data analysis

* object data analysis
* operator-valued kernels

* operator-based statistics

* joint-kernel maps
* statistical dynamics
* applications (non exhaustive list) : signal and image processing, bioinformatics, natural language processing, time series modeling …

Submission guidelines

Submissions should be written as extended abstracts, no longer than 4 pages in the ICML latex style. ICML style files and formatting instructions can be found at The submissions should include the authors’ name and affiliation since the review process will not be double blind. The extended abstract may be accompanied by an unlimited appendix and other supplementary material, with the understanding that anything beyond 4 pages may be ignored by the program committee. Please send your submission by email to nextgenkernelicml2012@gmail.com before May 7, 2102 at midnight PDT. Recently-published work is allowed.

We expect to select contributions for the spotlight and poster sessions. Authors will receive a notification by May 21, 2012.

Organizers

Florence d’Alché-Buc (University of Evry & INRIA-Saclay, France)
Hachem Kadri (INRIA-Lille, France)
Massimiliano Pontil (University College London, UK)
Alain Rakotomamonjy (University of Rouen, France)

Website admin: Céline Brouard (University of Evry, France)
Contact: nextgenkernelicml2012@gmail.com

Summer School on Domain Adaptation

Summer School on Domain Adaptation in Image Analysis:

The Summer School will be held in Copenhagen, Denmark from August 20-24th 2012. The school will present basic and advanced topics in domain adaptation through theoretical and practical lectures given by distinguished researchers in the field, among them Corinna Cortes, Mehryar Mohri, Yishay Mansour, and Trevor Darrell. All of them have strong experience in the topic of the Summer School. In addition, there will be lectures given by local members of the research group at DIKU.

We expect that the students finish the course with an apprehension of the variety of domain adaptation methods, and that they have been given the tools to tackle this learning problem in their own work. The lectures will be supplemented with practical exercises to deepen the students’ understanding of the material. In a plenum session, the invited experts will discuss future perspectives for the methods.

For further information, please visit the homepage of the Summer School (http://image.diku.dk/MLLab/SummerSchools/index.html). We hope to welcome you in Copenhagen.

Last call for papers – Eleventh International Symposium on Intelligent Data Analysis (IDA 2012)]

— — — — — — — — — — — — — — — —

Dear colleagues,

The Eleventh International Symposium on Intelligent Data Analysis
(IDA 2012) will be organized in Helsinki, Finland during 25-27 October,
2012. The call for papers is found at: http://ida2012.org/cfp.html

We are quickly approaching the submission deadline on May 12, 2012.

The submission system is open. The format of submissions is 11 pages
in the Springer LNCS format. More detailed information and the link
to the submission system can be found on: http://ida2012.org/submission.html

You may also follow news and updates on IDA 2012 in Twitter:
http://twitter.com/ida_news

On behalf of the IDA 2012 organizers,
Jaakko Hollmén

* * * * * * * * * * * * * * * * * * * * * * * * * * * *

CALL FOR PAPERS

The Eleventh International Symposium on
Intelligent Data Analysis (IDA 2012)

October 25-27, 2012, Helsinki, Finland

http://ida2012.org

* * * * * * * * * * * * * * * * * * * * * * * * * * * *

When the IDA symposium series started in 1995, it focussed on the
problem of end-to-end intelligent support for data analysis. In
2010, the IDA symposium re-focussed to support papers that go
beyond established technology and offer genuinely novel and
“game-changing” ideas, whilst not always being as fully realised as
papers submitted to other conferences. IDA 2012 continues this
approach and will include an important and still emerging class of
problems: the analysis of data from networked digital information
systems such as mobile devices, remote sensors, streaming
applications (e.g. Twitter), etc.

The IDA symposium seeks “first look” papers that might elsewhere be
considered preliminary but contain potentially high impact
research. The IDA symposium, which is A-ranked according to ERA, is
open to all kinds of modelling and analysis methods, irrespective
of discipline. It is expected to be an interdisciplinary meeting
that seeks abstractions that cut across domains. IDA 2012 welcomes
papers that focus on dynamic and evolving data, models, and
structures and the analysis of data from digital environments.

FRONTIER PRIZE

In line with the theme of IDA 2012, the IDA Frontier Prize will be
awarded to the most visionary contribution. Submissions considered
for this award must present novel and surprising approaches to data
analysis. The award consists of a plaque and a prize of 1000 Euros.

CALL FOR PAPERS

IDA solicits papers on all aspects of intelligent data analysis,
including papers on intelligent support for modelling and analyzing
data from complex, dynamical systems. IDA 2012 particularly
encourages papers about:

– Novel applications of IDA techniques to, e.g., digital environments
– Novel modes of data acquisition and the associated issues
– Robustness and scalability issues of intelligent data analysis techniques
– Visualization and dissemination of results

Intelligent support for data analysis goes beyond the usual
algorithmic offerings in the literature. Papers about established
technology will only be accepted if the technology is embedded in
intelligent data analysis systems, or is applied in novel ways to
analyzing and/or modelling complex systems.

The conventional reviewing process, which favours incremental
advances on established work, can discourage the kinds of papers
that IDA 2012 hopes to publish. The reviewing process will address
this issue explicitly: referees will evaluate papers against the
stated goals of the symposium, and any paper for which at least one
program chair advisor writes an informed, thoughtful, positive
review will be accepted irrespective of other reviews.

The proceedings of IDA 2012 will appear in Springer’s Lecture Notes
in Computer Science (LNCS) series. For more details on submission
and review process, see the IDA webpage at http://www.ida2012.org
or contact the program chairs. News and updates will be posted on the
IDA Twitter account @ida_news.

IMPORTANT DATES

Deadline for submissions: 12 May, 2012
Author notification: 14 July, 2012
Camera-ready papers due: 11 August, 2012
Conference dates: 25-27 October, 2012

INVITED SPEAKERS

Paola Sebastiani, Boston University, USA
Arno Siebes, University of Utrecht, The Netherlands
Gavin Cawley, University of East Anglia, United Kingdom

ORGANIZATION

General Chair:
Jaakko Hollmen, Aalto University, Finland

Program Chairs:
Frank Klawonn, Ostfalia University of Applied Sciences, Germany
Allan Tucker, Brunel University, United Kingdom

Poster Chair:
Frank Hoppner, Ostfalia University of Applied Sciences, Germany

Frontier Prize Chairs:
Elizabeth Bradley, University of Colorado, United States
Joao Gama, University of Porto, Portugal