SIMBAD 2015 - 3rd International Workshop on Similarity-Based Pattern Analysis and Recognition

3rd International Workshop on Similarity-Based Pattern Analysis and Recognition
October 12-14, 2015
Copenhagen, Denmark
http://www.dsi.unive.it/~simbad/2015/
MOTIVATIONS AND OBJECTIVES
Traditional pattern recognition and machine learning 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 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 such spaces offer powerful analytical as well as computational tools that are simply not available in other representations. This approach, however, 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 (dis)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. This shift in focus, however, 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 do not even obey the requirements of a metric. The lack of such properties undermines the very foundations of traditional pattern recognition and machine learning theories and algorithms and poses totally new theoretical and computational questions and challenges.
The aim of this workshop, following those held in Venice and York, 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 of course not limited to):
- Embedding and embeddability
- Graph spectra and spectral geometry
- Indefinite and structural kernels
- Game-theoretic models of pattern recognition
- Characterization of nonmetric behavior
- Foundational issues
- Measures of metric violations
- Learning and combining (dis)similarities
- Multiple-instance learning and other set-based approaches
- Applications
PAPER and ABSTRACT SUBMISSION
We allow three types of contributions.
Regular papers (not exceeding 16 pages LNCS format) must be submitted electronically. The submission site can be found through http://www.dsi.unive.it/~simbad/2015/index.php/pag.... All submissions will be subject to a rigorous peer-review process. Accepted papers will be published in Springer's Lecture Notes in Computer Science (LNCS) series.
In addition to regular, original contributions, we also solicit presentation of 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 only an abstract will be published. Submission of such contribution requires the additional submission of a two-page abstract in LNCS format with the original paper submitted as supplementary material.
Finally, we encourage the submission of two-page abstracts in general. These could contain preliminary results, topics for discussion, appeals for novel research directions, or anything else that suits the aim of SIMBAD and underlines the workshop character. Upon acceptance, these submissions will be assigned a poster presentation and the abstract will be published.
Submission implies the willingness of at least one of the authors to register and present the paper on acceptance.
INVITED SPEAKERS
TBA
IMPORTANT DATES
Submission of paper abstract: March 15, 2015
Submission of the final version of the paper: March 30, 2015
Submission of extended abstract only: April 15
Notifications: May 30, 2015
Camera-ready due: June 30, 2015
Conference: October 12-14, 2015
ORGANIZATION
Program Chairs
Aasa Feragen, University of Copenhagen, Denmark
Marco Loog, Delft University of Technology, The Netherlands
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 [provisional]
Ethem Alpaydin, Bogazici University, Turkey
ChloÈ-Agathe Azencott, Mines Paris Tech, France
Manuele Bicego, University of Verona, Italy
Joachim Buhmann, ETH Zurich, Switzerland
Tiberio Caetano, NICTA, Australia
Umberto Castellani, University of Verona, Italy
Veronika Cheplygina, Erasmus Medical Center, The Netherlands
Aykut Erdem, Hacettepe University, Turkey
Francisco Escolano, University of Alicante, Spain
Mario Figueiredo, Technical University of Lisbon, Portugal
Ana Fred, Technical University of Lisbon, Portugal
Edwin Hancock, University of York, UK
Soren Hauberg, Technical University of Denmark, Denmark
Christian Igel, University of Copenhagen, Denmark
Brijnesh Jain, Technical University of Berlin, Germany
Robert Krauthgamer, The Weizmann Institute of Science, Israel
Walter Kropatsch, Vienna University of Technology, Austria
Xuelong Li, Chinese Academy of Sciences, China
Yingyu Liang, Princeton University, USA
Vittorio Murino, Italian Institute of Technology, Italy
Antonio Robles-Kelly, NICTA, Australia
Fabio Roli, University of Cagliari, Italy
Luca Rossi, University of Birmingham, UK
Samuel Rota Bulo', Bruno Kessler Foundation, Italy
Volker Roth, University of Basel, Switzerland
Anastasios Sidiropoulos, Ohio State University, USA
Stefan Sommer, University of Copenhagen, Denmark
David Tax, Delft University of Technology, The Netherlands
Andrea Torsello, University of Venice, Italy
Richard Wilson, University of York, UK