Due to several requests, the submission deadline for SIMBAD 2013 has been postponed to:
>>> FEBRUARY 15, 2013 <<<
Please note that we're running a special issue of the IEEE Trans. on Neural Networks and Learning Systems on precisely the workshop's topics (submission deadline: October 2013), and we'll encourage the authors of the best workshop papers to submit.
Best regards
-mp
=================================
CALL FOR PAPERS
SIMBAD 2013
2nd International Workshop on Similarity-Based Pattern Analysis and Recognition
July 3-5, 2013
York, UK
http://www.dais.unive.it/~simbad
MOTIVATIONS AND OBJECTIVES
Traditional pattern recognition techniques are intimately linked to
the notion of "feature space." Adopting this view, each object is
described in terms of a vector of numerical attributes and is
therefore mapped to a point in a Euclidean (geometric) vector space so
that the distances between the points reflect the observed
(dis)similarities between the respective objects. This kind of
representation is attractive because geometric spaces offer powerful
analytical as well as computational tools that are simply not
available in other representations. However, the geometric approach
suffers from a major intrinsic limitation, which concerns the
representational power of vectorial, feature-based descriptions. In
fact, there are numerous application domains where either it is not
possible to find satisfactory features or they are inefficient for
learning purposes.
In the last few years, interest around purely similarity-based
techniques has grown considerably. For example, within the supervised
learning paradigm the well-established kernel-based methods shift the
focus from the choice of an appropriate set of features to the choice
of a suitable kernel, which is related to object similarities.
However, this shift of focus is only partial, as the classical
interpretation of the notion of a kernel is that it provides an
implicit transformation of the feature space rather than a purely
similarity-based representation. Similarly, in the unsupervised
domain, there has been an increasing interest around pairwise or even
multiway algorithms, such as spectral and graph-theoretic clustering
methods, which avoid the use of features altogether.
By departing from vector-space representations one is confronted with
the challenging problem of dealing with (dis)similarities that do not
necessarily possess the Euclidean behavior or not even obey the
requirements of a metric. The lack of such properties undermines the
very foundations of traditional pattern recognition theories and
algorithms, and poses totally new theoretical/computational questions
and challenges.
The aim of this workshop, which follows the one held in Venice in 2011
(http://www.dais.unive.it/~simbad/2011/), is to consolidate research
efforts in this area, and to provide an informal discussion forum for
researchers and practitioners interested in this important yet diverse
subject. We aim at covering a wide range of problems and perspectives,
from supervised to unsupervised learning, from generative to
discriminative models, and from theoretical issues to real-world
applications.
Original, unpublished papers dealing with these issues are solicited.
Topics of interest include (but are not limited to):
- Embedding and embeddability
- Graph spectra and spectral geometry
- Indefinite and structural kernels
- Game-theoretic models of pattern recognition
- Characterization of non-(geo)metric behavior
- Foundational issues
- Measures of (geo)metric violations
- Learning and combining similarities
- Multiple-instance learning
- Applications
PAPER SUBMISSION
All papers (not exceeding 16 pages) must be submitted electronically
at the conference website (http://www.dais.unive.it/~simbad/2013/).
All submissions will be subject to a rigorous peer-review process.
Accepted papers will appear in the workshop proceedings, which will be
published in Springer's Lecture Notes in Computer Science (LNCS)
series.
In addition to regular, original contributions, we also solicit papers
(in any LaTeX format, no page restriction) that have been recently
published elsewhere. These papers will undergo the same review process
as regular ones: if accepted, they will be presented at the workshop
but will not be published in the workshop proceedings.
Submission implies the willingness of at least one of the authors to
register and present the paper, if accepted.
INVITED SPEAKERS
Avrim Blum, Carnegie Mellon University, USA
Nello Cristianini, University of Bristol, UK
Frank Nielsen, Sony Computer Science Laboratories Inc, Japan
SPECIAL ISSUE OF IEEE TNNLS
A special issue of the IEEE Transactions on Neural Networks and Learning Systems on precisely the workshop's topics is scheduled for 2014 (submission deadline: October 2013). Authors of the best workshop papers will be encouraged to submit an extended version of their contribution.
IMPORTANT DATES
Paper submission: February 15, 2013
Notifications: March 30, 2013
Camera-ready due: April 25, 2013
Workshop: July 3-5, 2013
ORGANIZATION
Program Chairs
Edwin Hancock, University of York, UK
Marcello Pelillo, University of Venice, Italy
Steering Committee
Joachim Buhmann, ETH Zurich, Switzerland
Robert Duin, Delft University of Technology, The Netherlands
Mario Figueiredo, Technical University of Lisbon, Portugal
Edwin Hancock, University of York, UK
Vittorio Murino, Italian Institute of Technology, Italy
Marcello Pelillo (chair), University of Venice, Italy
Program Committee
Maria-Florina Balcan, Georgia Institute of Technology, USA
Manuele Bicego, University of Verona, Italy
Avrim Blum, Carnegie Mellon University, USA
Joachim Buhmann, ETH Zurich, Switzerland
Terry Caelli, NICTA, Australia
Tiberio Caetano, NICTA, Australia
Umberto Castellani, University of Verona, Italy
Luca Cazzanti, University of Washington, Seattle, USA
Nello Cristianini, University of Bristol, UK
Robert Duin, Delft University of Technology, The Netherlands
Aykut Erdem, Hacettepe University, Ankara, Turkey
Francisco Escolano, University of Alicante, Spain
Mario Figueiredo, Technical University of Lisbon, Portugal
Ana Fred, Technical University of Lisbon, Portugal
Mehmet Gonen, Aalto University School of Science, Finland
Marco Gori, University of Siena, Italy
Bernard Haasdonk, Universitaet Stuttgart, Germany
Edwin Hancock, University of York, UK
Robert Krauthgamer, Weizmann Institute of Science, Israel
Marco Loog, Delft University of Technology, The Netherlands
Marina Meila, University of Washington, Seattle, USA
Vittorio Murino, Italian Institute of Technology, Italy
Marcello Pelillo, University of Venice, Italy
Massimiliano Pontil, University College London, UK
Antonio Robles-Kelly, NICTA, Australia
Fabio Roli, University of Cagliari, Italy
Samuel Rota Bulo', University of Venice, Italy
Volker Roth, University of Basel, Switzerland
John Shawe-Taylor, University College London, UK
Andrea Torsello, University of Venice, Italy
Richard Wilson, University of York, UK
Lior Wolf, Tel Aviv University, Israel
