StarAI 2015 - Workshop on Statistical Relational Artificial Intelligence (StarAI)

UAI-15 Workshop on Statistical Relational Artificial Intelligence (StarAI), July 16th 2015, Amsterdam, The Netherlands.
Workshop Webpage: http://www.starai.org/2015
The purpose of the Statistical Relational AI (StarAI) workshop is to bring together researchers and practitioners from two fields: logical (or relational) AI and probabilistic (or statistical) AI. These fields share many key features and often solve similar problems and tasks. Until recently, however, research in them has progressed independently with little or no interaction. The fields often use different terminology for the same concepts and, as a result, keeping-up and understanding the results in the other field is cumbersome, thus slowing down research. Our long term goal is to change this by achieving a synergy between logical and statistical AI. As a stepping stone towards realizing this big picture view on AI, we are organizing the Fifth International Workshop on Statistical Relational AI at the Thirty-First Conference on Uncertainty in Artificial Intelligence (UAI).
PRACTICAL:
StarAI will be a one day workshop with around 50 attendees, paper presentations and poster spotlights, a poster session, and three invited speakers.
Those interested in attending should submit either a technical paper (AAAI style, 6 pages maximum) or a position statement (AAAI style, 2 pages maximum) in PDF format via the following EasyChair site:
https://easychair.org/conferences/?conf=starai2015
Key Dates:
* Papers due: May 15, 2015
* Notification: June 10, 2015
* Camera-ready due: July 1, 2015
* Day of Workshop: July 16, 2015
All submitted papers will be carefully peer-reviewed by multiple reviewers and low-quality or off-topic papers will be rejected. Papers will be selected either for a short oral presentation or a poster presentation.
For more information, please see the workshop website: http://www.starai.org/
INVITED SPEAKERS (tentative):
William Cohen (CMU, USA)
Kristian Kersting (TU Dortmund, Germany)
Sebastian Riedel (UCL, GB)
Dan Roy (University of Toronto, Canada)
TOPICS:
StarAI is currently provoking a lot of new research and has tremendous theoretical and practical implications. Theoretically, combining logic and probability in a unified representation and building general-purpose reasoning tools for it has been the dream of AI, dating back to the late 1980s. Practically, successful StarAI tools will enable new applications in several large, complex real-world domains including those involving big data, social networks, natural language processing, bioinformatics, the web, robotics and computer vision. Such domains are often characterized by rich relational structure and large amounts of uncertainty. Logic helps to effectively handle the former while probability helps her effectively manage the latter. We seek to invite researchers in all subfields of AI to attend the workshop and to explore together how to reach the goals imagined by the early AI pioneers.
The focus of the workshop will be on general-purpose representation, reasoning and learning tools for StarAI as well as practical applications. Specifically, the workshop will encourage active participation from researchers in the following communities: satisfiability (SAT), knowledge representation (KR), constraint satisfaction and programming (CP), (inductive) logic programming (LP and ILP), graphical models and probabilistic reasoning (UAI), statistical learning (NIPS and ICML), graph mining (KDD and ECML PKDD) and probabilistic databases (VLDB and SIGMOD). It will also actively involve researchers from more applied communities, such as natural language processing (ACL and EMNLP), information retrieval (SIGIR, WWW and WSDM), vision (CVPR and ICCV), semantic web (ICSW and ESWC) and robotics (RSS and ICRA).
ORGANIZING COMMITTEE:
Guy Van den Broeck (UCLA, KU Leuven, guyvdb-AT-cs.ucla.edu)
Mathias Niepert (Univeristy of Washington, mniepert-AT-cs.washington.edu)
Sriraam Natarajan (Indiana University, natarasr-AT-indiana.edu)
David Poole (University of British Columbia, poole-AT-cs.ubc.ca)