[Comp-neuro] Call for Papers - IJCAI’15 Workshop on Sensitivity Analysis and Robustness in Probabilistic Graphical Models

Alessandro Antonucci alessandro at idsia.ch
Fri Jan 16 09:46:47 CET 2015

IJCAI’15 Workshop on Sensitivity Analysis and Robustness 
Probabilistic Graphical Models
Buenos Aires, July 25-27, 2015 - 

Probabilistic graphical models are important tools in 
machine learning
and artificial intelligence for reasoning with 
uncertainty. They
provide means to represent large multivariate domains 
compactly and to
perform sophisticated learning and reasoning efficiently. 
Examples of
probabilistic graphical models are Bayesian networks, 
Markov Random
fields, chain and factor graphs, Gaussian graphical 
models, to name
but a few. The quantification of these models usually 
requires sharp
(i.e., precise) assessments of the model local potentials 
and might be
subject to robustness issues. For instance, perturbations 
of some
parameter values may lead to different decisions from 
those which
would be achieved by the unperturbed model, suggesting 
that decisions
are not reliable. Reliability might also be in question 
because of
missing data and assumptions behind the process.

The workshop invites submissions of papers on all aspects 
of sensitivity
analysis and robustness in probabilistic graphical models. 
may have a theoretical focus and/or an applied focus. A 
list of topics follows.

- Local and/or global sensitivity analysis.
- Parameter-based and/or decision-based sensitivity 
- Design of robust learning, inference and/or decision 
making approaches.
- Robust analysis and design of robustness measurements.
- Extensions of probabilistic graphical models.
- Reliable qualitative learning and reasoning.
- Robust treatment of missing data.
- Imprecise probability and other theories related to 
sensitivity analysis.
- Computational complexity, exact and approximate 

Each submission will be reviewed by peers using a 
double-blind process
(please use the third person in self citations and take 
all necessary
care not to identify yourselves). Accepted papers will be 
electronically in a volume of the JMLR Workshop and 
Proceedings series. There will be no rebuttal phase, but 
considered worth publishing and needing substantial 
revision might be
subject to a second round of reviewing/evaluation. All 
accepted papers
will be presented at the workshop. At least one of the 
paper's authors
should register and attend the workshop to present the 

Submissions must be formatted according to style and 
template files
available for the Journal of Machine Learning Research 
(JMLR) Workshop and
Conference Proceedings - two-column version. The style 
files are available at
Papers (including figures, tables, references, etc) are 
expected to have
between 6 and 10 pages.

Apr 27, 2015 - Deadline for submissions of contributions
May 20, 2015 - Workshop paper acceptance notification
May 30, 2015 - Deadline for workshop camera-ready copy (in 
case of minor
                revision; contributions needing major 
revision might need
                additional time - this will be arranged 
case by case)

Alessandro Antonucci*, IDSIA, Switzerland.
Alessio Benavoli, IDSIA, Switzerland.
Cassio P. de Campos*, Queen's University Belfast, UK.
Arthur Choi, University of California, Los Angeles, USA.
Giorgio Corani*, IDSIA, Switzerland.
Fabio Cozman, University of Sao Paulo, Brazil.
Adnan Darwiche, University of California, Los Angeles, 
Sebastien Destercke, Univ. de Technologie de Compiegne, 
Marek Druzdzel, University of Pittsburgh, USA.
Johan Kwisthout, Radboud University Nijmegen, The 
Agnieszka Onisko, Bialystok University of Technology, 
Denis Maua, University of Sao Paulo, Brazil.
Serafin Moral, Universidad de Granada, Spain.
Silja Renooij, Universiteit Utrecht, The Netherlands.
Matthias Troffaes, University of Durham, UK.
(*: Workshop organizers.)

More details about the submission procedure are available 
(We apologize in case you receive multiple copies of this
announcement, but yet we hope to reach the greatest 
number of people. Finding a trade-off is not an easy 

Alessandro Antonucci
Dalle Molle Institute
for Artificial Intelligence
Via Cantonale (Galleria 2)
CH-6928, Manno-Lugano, CH

mail: alessandro at idsia.ch
skype: alessandro.antonucci
tel: +41 916108515
web: www.idsia.ch/~alessandro

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