Fwd: IJCAI 2017 Workshop on Logical Foundations for Uncertainty and Learning

[Marcelo Finger]

IJCAI 2017 Workshop on Logical Foundations for Uncertainty and Learning

http://homepages.inf.ed.ac.uk/vbelle/workshops/lfu17/


Overview

The purpose of this workshop is to promote logical foundations for
reasoning and learning under uncertainty. Uncertainty is inherent in
many AI applications, and coping with this uncertainty, in terms of
preferences, probabilities and weights, is essential for the system to
operate purposefully. In the same vein, expecting a domain modeler to
completely characterize a system is often unrealistic, and so enabling
mechanisms by means of which the system can infer and learn about the
environment is needed. While probabilistic reasoning and Bayesian
learning has enjoyed many successes and is central to our current
understanding of the data revolution, a deeper investigation on the
underlying semantical issues as well as principled ways of extending
the frameworks to richer settings is what this workshop strives for.
Broadly speaking, we aim to bring together the many communities
focused on uncertainty reasoning and learning -- including knowledge
representation, machine learning, logic programming and databases --
by focusing on the logical underpinnings of the approaches and
techniques.


Given the intent of the workshop, we encourage two categories of submissions:


On the practical side, we solicit papers that propose ways to bridge
conventional learning and inference techniques with deductive and
inductive reasoning. Driven by the successes of relational graphical
models and statistical relational learning, we especially encourage
papers that emphasize or demonstrate non-standard logical features in
systems, e.g. the ability to handle infinite domains, existential
uncertainty and/or function symbols.

On the foundations side, we solicit papers that explicate the use of
weights in reasoning and learning, e.g. the use of weight functions
such as degrees of belief, preferences, and truth degrees. We
especially encourage papers that demonstrate how non-standard weight
functions for reasoning and learning can be better integrated with
existing probabilistic methods. The idea, then, is to foster
collaboration between machine learning practitioners and the weighted
logic community. For example, we encourage papers that revisit the
learning objectives and inference methodologies of existing systems,
and propose novel semantical frameworks to understand them.


In essence, this workshop builds on and extends the scope of the
successful series WL4AI (Weighted Logics for Artificial Intelligence:
ECAI-2012, IJCAI-2013, IJCAI-2015) in additionally looking at the
semantical foundations of machine learning and exploring practical
issues.


Topics include (but are not limited to):


Probabilistic and weighted databases and knowledge bases

Integration of deductive and inductive reasoning with Bayesian
inference and learning

Semantical foundations for machine learning

Logics for data-intensive information processing, such as data fusion

Extension of statistical relational learning with generic weight functions

Declarative methods for inference and learning


Paper Format and Submission


We invite technical papers (up to 6 pages), position papers (up to 2 pages).


We invite submissions describing either work in progress or mature
work that has already been published at other research venues and
would be of interest to researchers working on the themes above.
Submission of previously published work in whole or in part may be in
the form of a resubmission of a previous paper, or in the form of a
position paper that overviews and cites a body of work.


All papers should be typeset in the IJCAI style, described at

http://ijcai-17.org/FormattingGuidelinesIJCAI-17.zip



Papers should be submitted via EasyChair at
https://easychair.org/conferences/?conf=lfu17


Please see the website for up to date information (including
submission procedure):


http://homepages.inf.ed.ac.uk/vbelle/workshops/lfu17/



Important Dates


Paper Submission: May 15

Author Notification: June 8

Camera ready: July 15

Workshop Date: August 19



Organizing Committee


Vaishak Belle, University of Edinburgh, vaishak(at)ed.ac.uk

Marcelo Finger, University of Sao Paulo, mfinger(at)ime.usp.br

James Cussens, University of York, james.cussens(at)york.ac.uk

Guilin Qi, Southeast University, China, gqi(at)seu.edu.cn

Henri Prade, Universite Paul Sabatier, France, prade(at)irit.fr

Lluis Godo, IIIA CSIC, Spain, godo(at)iiia.csic.es


Program Committee


Fabio Cozman, University of Sao Paulo, Brazil

Jesse Davies, KU Leuven, Belgium

Adnan Darwiche, UCLA, USA

Didier Dubois, IRIT, France

Esra Erdem, Sabanci University, Turkey

Linda van der Gaag, Universiteit Utrecht, The Netherlands

Tommaso Flaminio, University of Insubria, Italy

Vibhav Gogate, University of Texas at Dallas, USA

Joe Halpern, Cornell University, USA

Manfred Jaeger, Aalborg University, Denmark

Souhila Kaci, University Montpellier, France

Gabriele Kern-Isberner, Technical University of Dortmund, Germany

Gerhard Lakemeyer, RWTH Aachen University, Germany

Churn-Jung Liau, Academia Sinica, Taiwan

Emiliano Lorini, IRIT, France

Thomas Lukasiewicz, University of Oxford, UK

Carsten Lutz, University of Bremen, Germany

Denis Maua, University of Sao Paulo, Brazil

Vanina Martinez, Universidad Nacional del Sur, Argentina

Zoran Ognjanovic, Mathematical Institute SANU, Serbia

Ron Petrick, Edinburgh, UK

Rodrigo De Salvo Braz, SRI, USA

Giuseppe Sanfilippo, Univ. Catania, Italy

Steven Schockaert, Cardiff University, UK

Guillermo Simari, Universidad Nacional del Sur, Argentina

Umberto Straccia, CNR, Italy

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.



--
Marcelo Finger
Departament of Computer Science, IME
University of Sao Paulo
http://www.ime.usp.br/~mfinger

[Marcelo Finger]