Bayes Lectures in Edinburgh, Aug 29-30 2012

The Schools of Mathematics and of Informatics at The University of Edinburgh are organizing a series of lectures on Bayesian statistics on Wed 29 and Thurs 30 August 2012. These lectures are named after the Reverend Thomas Bayes, a former student of the University of Edinburgh.

The invited lecturers are:
M J Bayarri (Universitat de València, Spain) Peter Grünwald (Centrum voor Wiskunde en Informatica, Netherlands) Jesper Møller (Aalborg University, Denmark) Aad van der Vaart (Leiden University, Netherlands)

This research workshop will run from 2pm on Wednesday 29 to 5pm on Thursday 30 August. In addition to the lectures there will be open discussion sessions. There are a number of places still open for attendance at the workshop. Participation is by invitation only. There may be a poster session on Wednesday if there is sufficient interest.
We encourage anyone who is interested to apply for an invitation by sending an email to bayes.lectures.edinburgh@gmail.com with the following information:

Name:
Affiliation:
Position:
Web site:
Dietary requirements for lunch:
Title and abstract of poster (optional):
Please describe briefly your reasons for requesting attendance:

For full consideration applications should be received by Thursday 26 July. There is no registration fee. However, we regret that we do not have funds available to cover the travel or accommodation of participants.

Website: http://conferences.inf.ed.ac.uk/bayeslectures/

Colin Aitken (School of Mathematics, University of Edinburgh) Natalia Bochkina (School of Mathematics, University of Edinburgh) Iain Murray (School of Informatics, University of Edinburgh) Chris Williams (School of Informatics, University of Edinburgh)

CALL FOR PAPERS: The 4th Asian Conference on Machine Learning (ACML2012)

Singapore, November 4-6, 2012

http://acml12.comp.nus.edu.sg/

======================================================================

The 4th Asian Conference on Machine Learning (ACML2012) will be held
on November 4-6, 2012, at the Singapore Management University,
Singapore. The conference aims at providing a leading international
forum for researchers in machine learning and related fields to share
their new ideas and achievements. Submissions from other than the
Asia-Pacific regions are also highly encouraged.

The conference program consist of tutorials, workshops, invited
keynote talks by distinguished researchers as well as single track
sessions of research paper presentations. The invited keynote speakers
for ACML 2012 are James Rehg (Georgia Tech), Dale Schuurmans
(University of Alberta), and Bob Williamson (Australian National
University and NICTA).

The proceedings will be published as a volume of Journal of Machine
Learning Research (JMLR): Workshop and Conference Proceedings. Authors
of selected papers will be invited to submit a significantly extended
version of their paper to a post-conference special issue of the
Machine Learning journal. The BEST STUDENT PAPER will receive an award
sponsored by the Machine Learning journal.

This year ACML will have a new feature: TWO submission deadlines. The
late deadline has the usual “accept” or “reject” outcomes. In addition
to the two outcomes, the early deadline also has “conditional accept
subject to required revisions”, and “resubmit” with notification in
time for them to make the final deadline. The authors of a submission
with a “conditional accept” decision are strongly encouraged to
carefully address the review comments in their revision. The revision
without addressing the review comments properly might be rejected. The
submission of “resubmit” decision must be significantly improved and
revised before it can be re-submitted in the late deadline. Fresh
submissions that have not caught up with the early deadline are also
welcome for the late deadline.

Important dates:
—————-
* Final Paper Submission: 24 July, 2012
* Final Notification: 8 Sept, 2012
* Camera ready: 24 Sept, 2012
* Conference: 4-6 November, 2012

ACML2012 calls for papers that report high quality original research
results on machine learning and related fields. The topics include but
are not limited to the following:

1. Learning problems

* Active learning
* Cost-sensitive Learning
* Ensemble methods
* Feature selection/extraction/construction
* Incremental learning and on-line learning
* Learning in graphs and networks
* Multi-agent learning
* Multi-instance learning
* Reinforcement learning
* Semi-supervised learning
* Supervised learning
* Classification, regression, ranking, structured, logical
* Transfer and multi-task learning
* Unsupervised learning
* Clustering, deep learning, latent variable models
* Other learning problems

2. Analysis of learning systems

* Computational learning theory
* Experimental evaluation methodology
* Others

3. Applications

* Bioinformatics
* Collaborative filtering
* Computer vision
* Information retrieval
* Mobile and pervasive computing
* Natural language processing
* Social networks
* Web search
* Other applications

4. Learning in knowledge-intensive systems

* Knowledge refinement and theory revision
* Multi-strategy learning
* Other systems

5. Other learning problems

Abstract and Paper Submission:
——————————
Electronic abstract and paper should be submitted through the ACML
2012 submission site:
https://cmt.research.microsoft.com/ACML2012/

Papers should be written in English and formatted according to the
JMLR Workshop and Conference Proceedings format
(http://jmlr.csail.mit.edu/proceedings/). The maximum length of papers
is 16 pages in this format. Overlength submissions or submissions
without appropriate format will be rejected without review. Paper
submissions should ensure double-blind reviews. Please be sure to
remove any information from your submission that can identify the
authors, including author names, affiliations, self citations and any
acknowledgments.

Proceedings will be published as a volume of JMLR: Workshop and
Conference Proceedings (this is not equivalent to a regular issue of
JMLR) at http://jmlr.csail.mit.edu/proceedings/

Papers submitted to this conference must not have been published,
accepted for publication or be under review for another conference or
journal. Novelty is an important criterion in the selection of
papers.

To encourage interdisciplinary contributions, ACML will welcome papers
that address applications of machine learning in other areas. For
these application papers, the novelty will be judged based on the
applications of machine learning methods. These papers will be
evaluated differently for the algorithmic papers. Authors of these
papers should choose “Applications” as the primary topic.

Submitting a paper to ACML 2012 means that if the paper is accepted,
at least one author will attend the conference to present the
paper. All papers must be submitted electronically in PDF format only,
before the deadline through the submission system. More information,
including detailed author instruction, is available at:
http://acml12.comp.nus.edu.sg/index.php?n=Main.CallForPapers

For questions and suggestions on paper submission, write to:
Steven Hoi < chhoi@ntu.edu.sg > or
Wray Buntine < wray.buntine@nicta.com.au >

Organizers
———-
General Co-Chairs
* Wee Sun Lee (National University of Singapore)
* Zhi-Hua Zhou (Nanjing University)

Program Co-Chairs
* Steven C.H. Hoi (Nanyang Technological University)
* Wray Buntine (NICTA)

Local Arrangement Co-Chairs
* Jing Jiang (Singapore Management University)
* Sintiani Dewi Teddy (Institute for Infocomm Research)
* Ivor Tsang (Nanyang Technological University)

Sponsorship Chair
* David Lo (Singapore Management University)

Finance Chair
* Jianxin Wu (Nanyang Technological University)

Tutorial Co-Chairs
* Hai Leong Chieu (DSO National Laboratories)
* Stanley Kok (Singapore University of Technology and Design)

Workshop Co-Chairs
* David Hardoon (SAS)
* Huan Xu (National University of Singapore)

Publication Chair
* Sinno Jialin Pan (Institute for Infocomm Research)

ACML Steering Committee
* Tom Detterich (Oregon State University, USA)
* Tu Bao Ho (JAIST, Japan)
* Hiroshi Motoda, Chair (Osaka University, Japan)
* Bernhard Pfahringer (Waikato University, New Zealand)
* Masashi Sugiyama (Tokyo Institute of Technology, Japan)
* Takashi Washio (Osaka University, Japan)
* Geoff Webb (Monash University, Australia)
* Qiang Yang (Hong Kong University of Science and Technology, Hong Kong)
* Zhi-Hua Zhou, Co-Chair (Nanjin University, China)

Senior Program Committee
* Edward Chang (Google Research Asia)
* Wei Fan (IBM TJ Watson Lab)
* Xaiofei He (Zhejiang University)
* Tu Bao Ho (JAIST, Japan)
* Chun-Nan Hsu (University of Southern California)
* Aapo Hyvarinen (Helsinki Institute for Information Technology)
* Rong Jin (Michigan State University)
* Kristian Kersting (University of Bonn)
* Irwin King (Chinese University of Hong Kong)
* James Kwok (Hong Kong University of Science and Technology)
* Pavel Laskov (University of Tubingen)
* Yuh-Jye Lee (NTUST)
* YoonKyung Lee (Ohio State University)
* Ping Li (Cornell University)
* Hang Li (Microsoft Research Asia)
* Phil Long (Google)
* Klaus-Robert Muller (Technical University Berlin)
* Bernhard Pfahringer (University of Waikato)
* Scott Sanner (Australian National University)
* Shirish Shevade (Indian Institute of Science)
* Masashi Sugiyama (Tokyo Institute of Technology)
* Jieping Ye (Arizona State University)
* Dell Zhang (Birbeck College University of London)
* Min-Ling Zhang (Southeast University)
* Xiaojin Jerry Zhu (University of Wisconsin (Madison)

CONFIDENTIALITY:This email is intended solely for the person(s) named
and may be confidential and/or privileged.If you are not the intended
recipient,please delete it,notify us and do not copy,use,or disclose
its content.

Towards A Sustainable Earth:Print Only When Necessary.Thank you.

Lambda Calculus and Differential Geometry and Big Iron

Seeking PhD students and postdocs interested in an elegant combination of functional programming and big-iron style numeric computing. (This project is, in truth, motivated by machine learning: I want to make it easy to implement complicated models, and to run them efficiently.)

Functional Programming and Automatic Differentiation

PhD Studentships
Postdoctoral Positions

We are adding exact first-class derivative calculation operators (Automatic Differentiation or AD) to the lambda calculus, and embodying the combination in a production-quality optimising compiler.
Our research prototype compiler generates object code competitive with the fastest current systems, which are based on FORTRAN. We are seeking PhD students and postdocs with interest and experience in relevant areas, such as programming language theory, numeric computing, machine learning, numeric linear algebra, differential geometry; and a burning drive to help lift big iron numeric computing out of the 1960s and into a newer higher order. Specific sub-projects
include: compiler and numeric programming environment construction; writing, simplifying, and generalising numeric and machine learning algorithms through the use of type theory and AD operators; and associated type/lambda calculus/PLT/real computation issues.

Project headquarters: Hamilton Institute, NUI Maynooth, Ireland, http://www.hamilton.ie/.

Applications and queries to:
Barak A. Pearlmutter barak+ad-fp-job@cs.nuim.ie

Action Recognition and Pose Estimation in Still Images Workshop at ECCV 2012, October 13, Firenze, Italy

http://vision.stanford.edu/apsi2012/index.html

Many human actions, such as “playing violin” and “taking a photo”, are well described by still images. Recognizing human actions and estimating human poses in still images will potentially provide useful information in image indexing and visual search, since a large proportion of available images contain people. Progress on these tasks is also beneficial to object and scene recognition, given the frequent human-object and human-scene interactions. Furthermore, as video processing algorithms often rely on some form of initialization from individual video frames, it would be interesting to have a better understanding of how, when, and to what extent static information can help recognize human actions and estimate human pose in videos. This workshop offers a great opportunity to bring together researchers and experts working on different aspects of action recognition and pose estimation to demonstrate their recent work. It provides a common playground for inspiring discussions and stimulating debates.

We invite high quality, original submissions for presentation during the workshop.
Contributions from the following areas are especially welcome:
• Human pose estimation in still images
• Human action recognition in still images • Modeling and recognition of human-object interactions • Scene context for human poses and actions • Understanding humans in videos or depth images • Novel datasets of human poses or actions • Actions and human pose research in cognitive psychology / human perception

Papers must be in PDF format and must not exceed 10 pages (ECCV format). All submissions are subject to a double-blind review process by the program committee.

• Deadline for submission of papers: July 3rd, 2012 • Notification of acceptance: August 2nd, 2012 • Camera-ready submission: August 8th, 2012 • Workshop date: October 13rd, 2012

The organizers can be contacted through apsi2012.ws@gmail.com

Open PhD position in machine learning and signal processing at Qarma, LIF, Marseille

We are looking for candidates for a three-year funded PhD entitled “Acceleration of greedy algorithms for signal modeling – Theory and applications” at Qarma, LIF, Marseille. See offer below, also available at http://www.lif.univ-mrs.fr/~vemiya/research/PhD_offer_Greta_Qarma.pdf .

Acceleration of greedy algorithms for signal modeling – Theory and applications

PhD position

Supervisors: Valentin Emiya and Liva Ralaivola, Laboratoire d’Informatique Fondamentale de Marseille, France

This PhD position is funded for three years.

PhD description

Keywords. Algorithms, machine learning, signal processing, optimization, sparsity.
Abstract. This PhD project addresses theoretical and applicative aspects of emerging sci- entific topics at the interface between machine learning and signal processing. The goal is to design new greedy algorithms, focusing on their speed.

Scientific context. Sparse approaches can model a wide range of signals – images, sounds,
biomedical signals, and so on – and their intrinsic structures. They benefit from a solid theory and efficient algorithms. These modern techniques are used in a growing number of applications such as signal compression and coding, source separation, inpainting or pattern recognition.
Goal. Today’s algorithms are limited by their computational complexity. As a result, they are slow and cannot handle large volumes of data. In practice, this is a major limitation since applications are more and more demanding e.g. in terms of real time constraints or fine 3D discretization. Recent theoretical results have opened new directions for the design of fast algo- rithms. In the case of greedy algorithms such as Matching Pursuit, preliminary theoretical and experimental results have been obtained at Laboratoire d’Informatique Fondamentale de Mar- seille (LIF). The goal of this PhD project is to develop this topic by designing new algorithms and validating them with theoretical and practical considerations. Several applications will be addressed such as audio inpainting and underwater acoustic imaging.

Tentative workflow. First, the PhD candidate will get familiar with sparse models and algorithms, and work on algorithmic ideas emerging from the preliminary results obtained at LIF. The research will be pursued in both the theoretical and the applicative direction, the focus being more on one or the other, depending on the candidate’s profile.

Collaborative context. The PhD project is at the core of a French ANR (national fund) project called GRETA (Greediness – theory and algorithms) initiated in 2012 by LIF, LATP and INSA Rouen. The PhD candidate will work within an active research group and will have the opportunity to travel inside and outside France, for conferences and collaborations.
Supervisors: Valentin Emiya and Liva Ralaivola, Qarma team, LIF.

Team and scientific environment
The PhD candidate will join the Qarma team at Laboratoire d’Informatique Fondamentale de
Marseille, which is a joint research lab between CNRS and Aix-Marseille University. The Qarma team (about twelve researchers) dedicates its activities to statistical machine learning theory and applications to signal processing and multimedia indexing.

The PhD candidate will also work with Sandrine Anthoine, a researcher at the neighboring mathematics lab. LATP. Other scientific exchanges will be possible locally and nationally (with the partners of the GRETA project, Rémi Gribonval at INRIA Rennes, Laurent Daudet at Paris 7 University, Jacques Marchal at Paris 6 University).
Required background

The applicant must have at least one of the following profiles: maths, signal processing, machine learning, computer science.

Salary
The candidate will be hired for three years with a standard French PhD contract (contrat doc- toral). The net salary is 1374.21 euros per month including health insurance. Teaching or consulting opportunities may be added to the contract if the candidate wishes.

Application
Applicants should contact Valentin Emiya and Liva Ralaivola (firstname.lastname@lif.univ-mrs. fr) as soon as possible. Additional information about the PhD project will be available at this stage.
The application must be sent by email to Valentin Emiya and Liva Ralaivola according to the schedule below. It must include

• a cover letter explaining the applicant’s motivations,
• a resume,
• a transcript of the Master degree marks (or equivalent), • optional: recommendation letters or referees contacts.

The selected applicants will be interviewed, either in the lab or by phone.
Schedule (subject to changes):

• June 30, 2012: deadline for sending the application.
• July 10, 2012: end of the interviews and announcement of the results. • October 1st, 2012: beginning of the contract.

Contact
Valentin Emiya and Liva Ralaivola, firstname.lastname@lif.univ-mrs.fr.

Post-doctoral Researcher in the area of data mining (Lugano, Switzerland)

A position for a post-doctoral data mining researcher is available at IDSIA (Lugano, Switzerland, www.idsia.ch).

**Duties
-Research and development of original data mining methods for classification, regression and clustering.
-Implementation of data mining algorithms within an existing Business Intelligence software program.

**Requirements
– Master’s Degree in computer science, statistics, physics, engineering or other highly quantitative areas.
-PhD in data mining related topics, or in statistical data modeling, preferably involving Bayesian networks.
-Strong publication record in the fields of data mining, machine learning or computational statistics.
-Strong commitment to research and scientific publication, together with the willingness to cooperate with a leading business intelligence company.
-Strong background in programming languages such as C++, C# or Java.
-Ability to produce high-quality data mining implementations, to efficiently analyze very large databases.
-Excellent oral and written English skills.

**We offer
-A two-year position with an employment contract of 100% and with the possibility of contract extension.
-International working environment.
-Collaboration with expert data mining researchers and with leading Business Intelligence companies.
-Participation in prominent international conferences, with the possibility for funded travel.
-Attractive salary, in line with Swiss employment standards.

**Applications
Applicants should submit the following documents, written in English:
– curriculum vitae
– list of exams and grades obtained in the course of studies conducted at Bachelor’s and Master’s level;
– names of three references (with e-mail addresses); -letter of motivation: brief statement on how the applicant’s research interests correspond with the above mentioned topics (1 – 2 pages); -list of publications, and, if possible, link to the thesis.

Completed applications should be submitted by the 5th July 2012 using the online form found at the following address:
www.supsi.ch/go/bando_data_mining_idsia

For further information please refer to the official page for this
position:
http://www.supsi.ch/home/supsi/lavora-con-noi/2012-07-05.html

or contact
Giorgio Corani
giorgio.corani@supsi.ch

*** MacBrain Symposium ***

http://macbrain2012.cs.ru.nl/
6 September 2012; Nijmegen, The Netherlands

A one day international symposium on the integrative analysis of brain diseases: brain banks, machine learning, clinical and pathological studies.

Speakers

* Jean-Paul Vonsattel – Director of the New York Brain Bank at Columbia University, USA
* Daniel Lightfoot – Director of the Autism Tissue Program, USA
* Sophia Ananiadou – Director of the National Centre for Text Mining, UK
* Yves Moreau – Program director of POC Bioinformatics Department of Bio-Engineering sciences, KU Leuven, Belgium
* Amanda Kiliaan – Department of Anatomy/Cognitive Neurosciences, Radboud University, NL
* John C. van Swieten – Erasmus MC, NL
* Inge Huitinga – Netherlands Brain Bank, NL
* Elena Marchiori – Radboud University, NL

Overview

The goal of this symposium is to provide researchers and practitioners an overview of the cutting edge research on core aspects of integrative research of brain diseases, combining data management, machine learning and clinical and pathological studies.
The lectures from worldwide domain experts will describe state-of-the-art research and discuss innovative directions aiming at optimizing knowledge discovery processes, from data collection in brain banks through machine learning to integrative clinical and pathological studies.

The symposium will provide a multi-disciplinary forum for discussing issues and
achievements in research on brain diseases. It will stimulate and strengthen synergy and collaboration among researchers from different disciplines, such as brain bankers, data managers, IT specialists, pathologists and clinicians, in order to improve the efficiency and effectiveness the integrative study of brain diseases.

Registration

Registration is on a first-come first-serve basis, so register as soon as possible at
http://macbrain2012.cs.ru.nl/registration. The registration fee for the MacBrain 2012 symposium is €50. It includes coffee/drinks and lunch.

Call for Papers: ECMLPKDD Workshop on Mining and exploiting interpretable local patterns

September 28, 2012, Bristol/UK
Submission deadline: June 29, 2012

Workshop homepage:
http://www.iais.fraunhofer.de/interpretable-patterns-workshop.html

———————————————————————–
Topics of interest:

* Actionable patterns
* Applications of local pattern mining, e.g. in clinico-genomic,
fraud detection or marketing settings
* Interactive data-mining
* Interpretable models
* Measures and optimization of interestingness for rules and models
* Pattern ordering and pattern set selection
* Scalability of local pattern mining
* Subgroup discovery

———————————————————————–
Submission details:

The papers must be written in English and formatted according to the Springer LNCS guidelines. Authors instructions and style files can be downloaded at: http://www.springer.de/comp/lncs/authors.html. The maximum length of the papers is 16 pages.

The complete submission process will be managed via Easy Chair:
https://www.easychair.org/conferences/?conf=ipat2012.

———————————————————————–
Detailed description:

Local patterns, like itemsets, correlations, contrast sets or subgroups, are valuable nuggets for a variaty of applications. Among others, they can been used for classification, regression or outlier detection tasks. One particular characteristic which makes them stand out from other machine learning tools, however, is that (most) local patterns can directly be read and interpreted by end users lacking a profound machine-learning background. This descriptive nature of local patterns makes them useful as a source of information for decision making. For example, in the analysis of clinical data, understandable models can help the clinician in understanding his data and thus making an informed decision about patient treatment. In addition, understandable knowledge can help domain experts to discuss the analysis results and collaboratively find a good, interesting solution in data-intensive settings to help guide the learner when complex background knowledge prevents the system from finding a good model without further input.

In this workshop, we wish to investigate typical use cases and key requirements for the successfull usage of local pattern mining in applications where next to the statistical performance of models, the understandability and interestingness of the models is the key success factor. Here, we are particularly interested in settings where the data to be mined is large and complex, preventing investigations of the data without (semi-)automatic analysis tools. Key questions to be investigated in the workshop are: which pattern language is adequate both for the representation of local phenomena and for the interpretation by the user. How can the raw set of local patterns be reduced to a representative and manageable subset?
What conditions must be satisfied for a pattern to be actionable?
How can feedback about the understandability and interestinness of partial models be given back to the system and how can the search be controlled? What is the best way to deal with the (typically exponential) size of the pattern space? How to design scalable algorithms? Beside papers focusing on such questions, we welcome case studies of successful descriptive pattern mining applications. Papers combining applications and theoretical contributions are particularly welcome.

PRELIMINARY CALL FOR PAPERS – IbPRIA 2013 – 6th Iberian Conference on Pattern Recognition and Image Analysis

Madeira, Portugal
June 5-7, 2013
http://www.ibpria.org/2013

The Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) is an international event co-organised every two years, by the Portuguese and Spanish Associations for Pattern Recognition.

IbPRIA is a single track conference that includes tutorials, invited speakers as well as oral and poster presentations. The conference is intended to act as a forum for research groups, engineers and practitioners to present recent results, algorithmic improvements and promising future directions in pattern recognition and image analysis.

SCOPE
The conference is looking for new theoretical results, techniques and main applications on any aspect of pattern recognition and image analysis, including but not restricted to the following topics:

Pattern Recognition
Image Analysis
Computer Vision
Multimedia Systems
Statistical and Structural Pattern Recognition
Machine Learning and Data Mining
Bioinformatics
Image Coding and Processing
Shape and Texture Analysis
Information Systems
Biometric Technologies
Speech Recognition
Document Processing
Character and Text Recognition
Robotics
Remote Sensing
Industrial Applications of Pattern Recognition
Special Hardware Architectures

PAPER SUBMISSION
Papers should describe original and unpublished work on the topics of the conference. Prospective authors should prepare a full paper, written in english, not exceeding 8 pages and must submit it electronically. Further information can be found on the conference website: http://www.ibpria.org/2013
Each paper will be blind-reviewed by at least two reviewers and will be accepted based on its originality, signficance and clarity. All accepted papers will appear in the conference proceedings, scheduled to be published in Springer LNCS series. A copy of the proceedings will be distributed to all participants at the Conference.
Moreover, the IbPRIA 2013 conference provides additional opportunities for journal publicaction and best paper awards. Contacts are being established with an indexed journal for a special issue.
Submission implies that at least one of the authors has to register and to present the communication at the conference if the paper is accepted.

IMPORTANT DATES (TENTATIVE)

Submission of papers: November 19, 2012
Notification of acceptance: January 19, 2013
Camera-Ready: February 2, 2013
For more information please visit http://www.ibpria.org/2013

Open PhD position at the ERIC Lab in Lyon, France

A PhD position is now open at the ERIC Lab for the development of “New graphical models for temporal clustering”. All applications are welcome, with an expected start date about the 1st of September or the 1st of October 2012. Detailed description of the PhD is available here:

http://eric.univ-lyon2.fr/~jvelcin/public/misc/phd-Imagiweb-en.pdf (english version)
http://eric.univ-lyon2.fr/~jvelcin/public/misc/these-Imagiweb-fr.pdf (french version)

Deadline for application: 8th of July, 2012.