[Dgkl] SECOND CALL FOR PAPERS, PLP 2023: The Tenth Workshop on Probabilistic Logic Programming

Kilian Rueckschloss kilian.rueckschloss at lmu.de
Wed Apr 26 13:20:29 UTC 2023


Dear Sir or Madam,


please distribute the following Call for Papers within your network.

Thank you!


Best regards,

Kilian Rückschlos & Felix Weitkämper
Programme Committee Chairs


=========================================================================

                          SECOND CALL FOR PAPERS
     PLP 2023: The Tenth Workshop on Probabilistic Logic Programming

=========================================================================

    A Workshop of 39th International Conference on Logic Programming
                        July 09-15, 2023

=========================================================================

** New Deadline for submissions:  May 08th, 2023
** Submission Link: https://easychair.org/conferences/?conf=plp2023
** Workshop Webseite: https://stoics.org.uk/~plp2023/

Overview
********

Probabilistic logic programming (PLP) approaches have received much
attention in this century. They address the need to reason about
relational domains under uncertainty arising in a variety of
application domains, such as bioinformatics, the semantic web,
robotics, and many more. Developments in PLP include new languages
that combine logic programming with probability theory, as well as
algorithms that operate over programs in these formalisms.

The workshop encompasses all aspects of combining logic, algorithms,
programming and probability.

PLP is part of a wider current interest in probabilistic
programming. By promoting probabilities as explicit programming
constructs, inference, parameter estimation and learning algorithms
can be run over programs which represent highly structured probability
spaces. Due to logic programming's strong theoretical underpinnings,
PLP is one of the more disciplined areas of probabilistic
programming. It builds upon and benefits from the large body of
existing work in logic programming, both in semantics and
implementation, but also presents new challenges to the field. PLP
reasoning often requires the evaluation of large number of possible
states before any answers can be produced thus breaking the sequential
search model of traditional logic programs.

While PLP has already contributed a number of formalisms, systems and
well understood and established results in: parameter estimation,
tabling, marginal probabilities and Bayesian learning, many questions
remain open in this exciting, expanding field in the intersection of
AI, machine learning and statistics.

As is traditional in this series, the workshop would be designed to
foster exchange between the various communities relevant to probabilistic
logic programming, including probabilistic programming and statistical
relational artificial intelligence. More precisely, the workshop is open
to new, preliminary and recently published work in all areas related to
probabilistic logic programming, including but not limited to

* probabilistic (logic) programming formalisms
* probabilistic (logic) programming languages
* parameter estimation
* statistical inference
* implementations
* structure learning
* reasoning with uncertainty
* constraint store approaches
* stochastic and randomised algorithms
* probabilistic knowledge representation and reasoning
* neuro-symbolic representation and reasoning
* constraints in statistical inference
* PLP applications, such as bioinformatics, semantic web, robotics,...
* lifted probabilistic graphical models
* (lifted) Bayesian learning
* tabling for learning and stochastic inference
* sampling methods
* stochastic search
* labelled logic programs
* weighted model counting
* knowledge compilation
* integration of statistical software

This list is by no means exhaustive.

Purpose
********

After nine successful editions of this workshop, the tenth edition
of PLP will be held at the ICLP conference organised by the
Imperial College London. We hope that this encourages further
collaboration between researchers in PLP and researchers working in
other areas of ICLP.

Submissions
***********

Submissions will be managed via EasyChair 
(https://easychair.org/conferences/?conf=plp2023).
Contributions should be prepared in the LNCS style
(https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). 

A mixture ofpapers are sought including: new results; work in progress; and
technical summaries of recent substantial contributions.  Papers
presenting new results should be 6-15 pages in length. Work in
progress and technical summaries can be shorter (2-5 pages).

At least one author of each accepted paper will be required to attend
the workshop to present the contribution.

Publication
***********

Informal proceedings will be made available electronically to
attendees and submitted to the CEUR Workshop Proceedings repository
(http://ceur-ws.org/).

Deadlines
*********

Papers due: May 08th, 2023
Notification to authors: June 8th, 2023
Camera ready version due: June 19th, 2023
Workshop date: September  July 09-15, 2023

(all dates are AoE)


Invited Speaker(s)
******************


Dr. Devendra Singh Dhami, Independent Research Group Leader and Post 
Doctoral Researcher, hessian.AI and AIML Lab, TU Darmstadt
Prof. Rafael Peñaloza, Associate Professor, University of Milano-Bicocca
Prof. Joost Vennekens, Associate Professor, KU Leuven


Programme Committee Chairs
**************************

Kilian Rückschloß (Ludwig-Maximilians Universität München, Germany)
Felix Weitkämper (Ludwig-Maximilians Universität München, Germany)

Programme Committee
*******************

Rafael Kiesel, TU Wien
Sagar Malhotra, FBKI Trento
Dr. Nico Potyka, Imperial College London
Dr. Vaishak Belle, University of Edinburgh
Prof. Elena Bellodi, Associate Professor, University of Ferrara
Prof. Fabio Cozman, Full Professor, Universidade de São Paulo
Dr. Matthias Nickles, Lecturer Above the Bar, NUI Galway
Dr. Roberta Calligari, Postdoc, Università di Bologna
Prof. Fabrizio Riguzzi, University of Ferrara
Dr. Damiano Azzolini, University of Ferrara
Dr. Peter Baumgartner, Data61/ANU canberra
Theresa Swift PhD, Universidad Nova de Lisboa



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