Postdoctoral Position in Machine Learning with,application to Computer Vision at KTH, Stockholm, Sweden

A postdoctoral position in Machine Learning with application
to Computer Vision is available in the Computer Vision group
(CVAP) at KTH, Stockholm.

The position will be associated with an ongoing project in,
Computer Vision that can be either:

1. Wearable Visual Information Systems

http://www.nada.kth.se/cvap/vinst.html

This project aims at the processing of visual information captured in
wearable cameras. The main objectives are recognition, classification,
location finding in e.g. mobile phone cameras as well as the automatic
creation of visual diaries from continuously wearable cameras.

2. Capturing and Visualizing Large Scale Human Action

http://www.csc.kth.se/~sullivan/actvis/results.html

This project is also closely associated with the European project
FINE. http://www.projectfine.eu/

This project has as its main goal the mapping of human sports action
from video into 3D animations. Specifically we will consider the 3D
capture of players actions in football games. The project is carried
out in connection with the Swedish industrial partner TRACAB as well as
other industrial partners in Europe.

The length of the position is 2 years with possible extension up to 4
years. The applicant is expected to perform full time research of
which approximately 50% will be devoted to the associated project.

Applications should include a cover letter indicating the associated
research project of interest, a curriculum vitae, and the contact
information of references.

The position is part of a larger (3) post-doc program at KTH

Please follow the link:
http://www.kth.se/om/work-at-kth/vacancies/postdoctoral-positions-in-machine-learning-1.62352?l=en_UK

for detailed instructions of application

Deadline for application is October 1st 2010

For information contact:
Stefan Carlsson, stefanc at csc.kth.se, Tel: +46 8 790 8432
Josephine Sullivan sullivan at csc.kth,se +46 8 790 6136

Book Announcement: “Reinforcement Learning and Dynamic Programming Using Functions Approximators”

Dear machine learning researchers,

We are pleased to announce the recent release of our book:
“Reinforcement Learning and Dynamic Programming Using Functions Approximators”
(Lucian Busoniu, Robert Babuska, Bart De Schutter, and Damien Ernst)
in the Automation and Control Engineering series of Taylor & Francis CRC Press.

Book information:

Reinforcement learning (RL) can optimally solve decision and control problems involving complex dynamic systems, without requiring a mathematical model of the system. If a model is available, dynamic programming (DP), the model-based counterpart of RL, can be used. RL and DP are applicable in a variety of disciplines, including artificial intelligence, automatic control, economics, and medicine. Recent years have seen a surge of interest RL and DP using compact, approximate representations of the solution, which enable algorithms to address realistic problems.

This book provides an in-depth introduction to RL and DP with function approximators, with a focus on continuous-variable control problems. A concise description of classical RL and DP (Chapter 2) builds the foundation for the remainder of the book. This is followed by an extensive review of the state-of-the-art in RL and DP with approximation, which combines algorithm development with theoretical guarantees, illustrative numerical examples, and algorithm comparisons (Chapter 3). Each of the final three chapters (4 to 6) is dedicated to a representative algorithm from the authors’ research. These three algorithms respectively belong to the three major classes of methods: approximate value iteration, approximate policy iteration, and approximate policy search. The features and performance of these algorithms are highlighted in comprehensive experimental studies on a range of control applications.

Features:
* A concise introduction to the basics of RL and DP
* A detailed treatment of RL and DP with function approximators, including theoretical results and illustrative examples
* A thorough treatment of policy search techniques
* Comprehensive experimental studies on a range of control problems, including real-time control results
* An extensive, illustrative convergence and consistency analysis of an approximate value iteration algorithm

For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work.

Access the book’s website at http://www.dcsc.tudelft.nl/rlbook/ for additional information, including computer code used in the experimental studies, information about ordering the book, etc.

Hoping you will find this book useful,

Sincerely,

The authors

Job opening: Research Fellow in Machine Learning and Corpus Classification

The Centre for Translation Studies, University of Leeds, UK, is inviting
applications for a Research Fellow post to work on a research project
funded by an FP7 grant from the European Commission. It is a full-time,
fixed term position to be filled as soon as possible, lasting until
31 Dec 2012.

We’re interested in a candidate with a PhD in Computational linguistics
or Machine Learning and experience in designing ML algorithms for text
categorisation tasks. For a formal application, take a look at the job
description:
http://hr.leeds.ac.uk/jobs/ViewJob.aspx?SId=16&JId=1306

I will be attending ACL2010 in Uppsala and SIGIR2010 in Geneva, so feel
free to contact me there informally.

Closing date for applications: 03 August 2010
Salary: Grade 7 (£29,853 – £35,646 p.a)
It is likely that an appointment will be made at or below £30,747 p.a.
since there are funding limitations which dictate the level at which the
appointment can start.

Call for participation: The Fifth European Workshop on Probabilistic Graphical Models (PGM’2010), Helsinki

The Fifth European Workshop on Probabilistic Graphical Models (PGM’2010)
Helsinki, Finland, September 13-15, 2010
http://www.helsinki.fi/pgm2010/

News:
====
* Deadline for early registration is Friday August 6
* Registration is open at
http://www.helsinki.fi/pgm2010/registration.html
* Invited speakers and list of accepted papers:
http://www.helsinki.fi/pgm2010/programme.html

The European Workshop on Probabilistic Graphical Models (PGM) is a biennial workshop that aims to bring together people interested in probabilistic graphical models and provides a forum for discussion of the latest research developments in this field. The first PGM workshop was first held in Cuenca, Spain, in 2002, followed by workshops in Leiden (2004), Prague (2006) and Hirtshals (2008). The fifth PGM workshop will be held in Helsinki, Finland, September 13-15, 2010.

Welcome!

Programme Co-Chairs:
Petri Myllymäki, University of Helsinki
Teemu Roos, Helsinki Institute for Information Technology HIIT
Tommi Jaakkola, MIT

Contact: pgm2010 at helsinki.fi
Home page: http://www.helsinki.fi/pgm2010/

Call for posters: Workshop on Validation in Statistics and Machine Learning

October, 6 – 7, 2010
WIAS Berlin, Germany

http://www.wias-berlin.de/workshops/validation2010/

— Important dates —

* submission deadline (posters): 31 Aug
* notification of submissions : 08 Sep
* registration deadline : 22 Sep

— Overview —

In statistics and machine learning, the evaluation of algorithms
typically relies on their performance on data. This is because, in
contrast to a theoretical guarantee (e.g. a consistency result), it is
in general not possible to prove that an algorithm performs well on a
particular (unseen) data set. Therefore, it is of vital importance that
we ensure the reliability of data-based evaluations. This requirement
poses a wide range of open research problems and challenges. These include

* the lack of a ground truth to validate results in real-world
applications,
* the high instability of empirical results in many settings,
* the difficulty to make statistics and machine learning research
reproducible,
* the general over-optimism of published research findings due
pre-publication optimization of the algorithms and publication bias.

This workshop brings together scientists from statistics, machine
learning, and their application fields to tackle these challenges. The
workshop serves as a platform to critically discuss current
shortcomings, to exchange new approaches, and to identify promising
future directions of research.

We invite poster submissions that fit into the scope and topics of the
workshop.

The workshop is funded by the Weierstrass Institute (WIAS) Berlin and by
the Pascal2 Network of Excellence.

Invited speakers include:

Mikio L. Braun (TU Berlin)
Thorsten Dickhaus (HU Berlin)
Francois Fleuret (EPF Lausanne / IDIAP)
Thomas A. Gerds (University of Copenhagen)
Jelle Goeman (Leiden University)
Ulrike Grömping (Beuth University of Applied Sciences Berlin)
Torsten Hothorn (LMU Munich)
Niels Keiding (University of Copenhagen)
Ulrich Mansmann (LMU Munich)
Carolin Strobl (LMU Munich)
Richardus Vonk (Bayer-Schering Pharma)

— Organization —

Nicole Krämer (WIAS Berlin)
Anne-Laure Boulesteix (University of Munich)

Multiple Positions in Robotics/Vision/Learning at U. Innsbruck

In a new research group in Intelligent Systems at the University of
Innsbruck, to be directed by Prof. Justus Piater, multiple positions
will shortly be available for postdoctoral researchers and doctoral
students.

* Our Opportunities

These (non-permanent) university research staff positions are not tied
to any specific research projects. Research topics are negotiable
within the range of activities of the research group. Topics of
particular interest include:

– gesture-based human-computer interaction
– video analysis for sign language transcription
– semantic understanding of observed manipulative actions
– exploratory learning from sensorimotor to conceptual levels
– learning to learn: leverage experience to guide future learning
– perception and inference for robotic grasping and manipulation
– landmark-based visual SLAM
– reactive algorithms for obstacle avoidance and navigation

Most of these topics tie in with one active and two upcoming
EU-FP7-ICT projects in Cognitive Systems, Interaction and Robotics,
offering a vibrant and internationally well-connected research
environment.

Postdoctoral researchers are expected to assume leadership roles.
In addition, all positions involve minor teaching requirements.

Salaries are internationally competitive and commensurate with
qualification and experience.

* Your Profile

Applicants for a postdoctoral position should have earned, or be about
to earn, a doctoral degree in a relevant area, possess a strong
publication record commensurate with experience, and have demonstrated
strengths in at least one of the following areas:

– statistical machine learning
– probabilistic modeling and inference
– computer vision
– robotic grasping or manipulation
– autonomous mobile robotics

Applicants for a doctoral studentship should have earned, or be about
to earn, an M.Sc. degree or equivalent in a relevant area, possess an
excellent academic record, and have demonstrated prior achievements in
any of the above areas.

All applicants should possess good written and oral communication
skills in English, a strong mathematical background, and programming
experience. Enthusiasm for leading-edge research, a team spirit and
independent problem-solving skills are essential.

* The University of Innsbruck, Austria

The history of the University of Innsbruck dates back to 1669. It
offers a complete set of academic curricula and currently counts 25000
students. Founded in 2001, the Department of Computer Science is
currently expanding and is highly active in research.

Innsbruck is home to about 30000 students who imprint a distinctive,
international student atmosphere upon this beautiful city of 120000.
Beautifully located in the Tyrolean Alps, on the Inn river and
surrounded by peaks of up to 2718m, Innsbruck offers outstanding
recreational and cultural value all around the year.

* How to Apply

Interested applicants should send a letter of motivation, a curriculum
vitae, scanned transcripts and diplomas, and contact information of at
least two references as a single PDF file to Justus.Piater at ULg.ac.be.

Applications will be considered as they are received, until all
positions are filled. The earliest possible starting date is
September 15.

ICGI 2010

10th International Colloquium on Grammatical Inference

ICGI 2010

13-16 September, 2010 Valencia (Spain)

http://users.dsic.upv.es/workshops/icgi2010/

SCOPE AND LOCATION
==================

ICGI 2010 is the tenth edition of the International Colloquium on Grammatical
Inference series which is a biennial conference being considered the most
successful conference related to Grammatical Inference.

The conference will take place at the city of Valencia which is the third
largest city in Spain. Valencia is a beautiful city in the Mediterranean coast
where centenary traditions live together with modernity. Its climate is
mediterranean with mild winters and hot summers. The city contains a dense
monumental heritage together with the City of Arts and Sciences an avant-garde
and futuristic museum complex.

The conference is colocated with the European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD
2010) which will take place in Barcelona, from September 20th to 24th, 2010.

This edition is a celebration one due to the 10th anniversary. We are planning
some innovations with respect to previous editions such as a tutorial day,
special talks and an award to the best student paper.

TUTORIAL DAY
============

On September 13th, the tutorial day will be held. The following lecturers and
topics are confirmed:

* Graph Grammars: Representations, Algorithms, and Induction
Tim Oates, with Sourav Mukherjee (University of Maryland Baltimore
County, USA)

* Active Learning
Colin de la Higuera (University of Nantes, France)

* Modelling Biological Sequences by Grammatical Inference
Francois Coste (INRIA/IRISA, France)

* Inference of Finite Automata
Damián López, with Pedro García (Universidad Politécnica de Valencia, Spain)

INVITED LECTURES
================

* Molecules, Languages, and Automata
Dr. David B. Searls (University of Pennsylvania, USA)

* Grammatical Inference and Games
Dr. Simon Lucas (University of Essex, UK)

CONFERENCE AND PROGRAM COMMITTEE CHAIR
======================================

José M. Sempere (Universidad Politécnica de Valencia, Spain)

PROGRAM COMMITTEE
=================

Pieter Adriaans, (Universiteit van Amsterdam, The Netherlands)
Dana Angluin, (Yale University, USA)
Jean-Marc Champarnaud, (Université de Rouen, France)
Alexander Clark, (Royal Holloway University of London, United Kingdom)
Francois Coste, (INRIA, France)
Francois Denis, (Université de Provence, France)
Henning Fernau, (Universität Trier, Germany)
Pedro García, (Universidad Politécnica de Valencia, Spain)
Colin de la Higuera, (Jean Monnet University in Saint-Etienne, France)
Makoto Kanazawa, (National Institute of Informatics, Japan)
Satoshi Kobayashi, (University of Electro-Communications, Japan)
Laurent Miclet, (ENSSAT-Lannion, France)
Tim Oates, (University of Maryland Baltimore County, USA)
Arlindo Oliveira, (Lisbon Technical University, Portugal)
Jose Oncina, (Universidad de Alicante, Spain)
Georgios Paliouras (Institute of Informatics Telecommunications, Greece)
Yasubumi Sakakibara, (Keio University, Japan)
Etsuji Tomita, (University of Electro-Communications, Japan)
Menno van Zaanen, (Tilburg University, The Netherlands)
Ryo Yoshinaka, (Hokkaido University, Japan)
Sheng Yu, (The University of Western Ontario, Canada)
Thomas Zeugmann, (Hokkaido University, Japan)

ORGANIZATION COMMITTEE
======================

Marcelino Campos, (Universidad Politécnica de Valencia, Spain)
Antonio Cano, (Universidad Politécnica de Valencia, Spain)
Damián López, (Universidad Politécnica de Valencia, Spain)
Alfonso Muñoz-Pomer, (Universidad Politécnica de Valencia, Spain)
Piedachu Peris, (Universidad Politécnica de Valencia, Spain)
Manuel Vázquez de Parga, (Universidad Politécnica de Valencia, Spain)

Research position at UCL, London

Research Associate in Statistics, – Ref:1151366

UCL Department / Division: Statistical Science
Grade 7
Hours: Full Time
Salary (inclusive of London allowance): £31,778-£38,441 per annum

Duties and Responsibilities

To develop novel methodology for multiple time series, as well as adapting
the theory to the analysis of neuroscientific and other applied time
series problems in collaboration with other departments in UCL.
The post is funded by EPSRC initially for three years.

Key Requirements

A strong background is required in one or more of mathematical statistics,
statistical methodology and machine learning. Some experience of
programming, signal processing and/or applied statistics experience would
be advantageous. Applicants must have, or expect to obtain in the near
future, a PhD in a relevant discipline.

Further Details

Further details of the project including a job description and person
specification can be accessed at the bottom of the page.
Information about the Department of Statistical Science can be found at
http://www.ucl.ac.uk/Stats. If you have any queries regarding the
vacancy, or the application process, please contact Professor Sofia
Olhede, s.olhede at ucl.ac.uk

Closing Date: 1 Oct 2010
Latest time for the submission of applications: 5pm
Interview date: TBA
This appointment is subject to UCL Terms and Conditions of Service for
Research and Support Staff. Please go to
http://www.ucl.ac.uk/hr/salary_scales/Support_Research_tcs.php to view the
terms and conditions.

Advertisement on UCL homepages

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Research Position at Xerox Research Centre Europe, Grenoble

Research Scientist in Text Mining
———————————-

The Cross-Language Technologies (CLT) group of the Xerox Research Centre
Europe conducts research in Statistical Machine Translation and in Information
Retrieval, Categorization and Clustering using advanced machine learning methods.

The group is looking for a talented researcher with skills than can both integrate well
and complement the current team. The ideal profile is:
• Ph.D in Mathematics (Statistics), Natural Language Processing or Computer Science;
• Strong skills in machine learning and statistical techniques applied to text mining and
sequence mining;
• A good command of English written and oral communication skills is required, as well
as open-mindedness and the will to collaborate with a team.

The successful candidate will be in charge of designing, developing and implementing text
categorization, clustering and segmentation methods, as extensions of our current portfolio
of technologies. She/he will interact with operational departments and customers, in order
to enhance all forms of business validation of the research results, technology transfers towards
development teams and “customer-driven’’ research.

Starting date : September 2010
Duration : 18 months

Please email your CV and cover letter, with message subject “Text Mining Researcher” to
xrce-candidates and to Jean-Michel.Renders at xrce.xerox.com.

Inquiries can be addressed to Jean-Michel.Renders at xrce.xerox.com

Extended announcement:

http://www.xrce.xerox.com/About-XRCE/Career-opportunities/Research-Scientist-in-Text-Mining

CFP: Workshop “ZULU Competition Debriefing”

Workshop “ZULU Competition Debriefing”

Satellite Event to the
10th International Colloquium on Grammatical Inference (ICGI’10)

Valencia, Spain, September 16th, 2010.

http://users.dsic.upv.es/workshops/icgi2010/
http://labh-curien.univ-st-etienne.fr/zulu/

Supported by Pascal 2 Network of Excellence

Zulu was a active learning competition, where participants were to build
algorithms that can learn deterministic finite automata (DFA) by making
the smallest number of membership queries to a server/oracle
(seehttp://labh-curien.univ-st-etienne.fr/zulu/). The competition
took place during the month of July 2010.

The results of the competition make it clear that a substancial
improvement of the state of the art has taken place. In order to
analyse and discuss this progress, but also to comment upon the
competition and give the prizes to the winner, a workshop inside
ICGI will be organised on the last day of ICGI 2010
(http://users.dsic.upv.es/workshops/icgi2010/).

CALL FOR SUBMISSION

Participants to the Competition are encouraged to submit an extended
abstract (~2-4 pages in PDF) in which they present their analysis and
algorithms. Researchers that have not participated are also allowed to
submit an abstract, when within the scope of Zulu. These papers should be
mailed to Jean-Christophe Janodet (mailto:janodet@univ-st-etienne.fr). *
Deadline for submission of papers: July 23rd, 2010
* Notification of acceptance: July 30th, 2010
* Workshop date: September 16th, 2010