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<span style="font-kerning: none" class="">CALL FOR PAPERS and PARTICIPANTS</span></div>
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<span style="font-kerning: none" class="">2nd International Workshop on Declarative Learning Based Programming (DeLBP 2017) </span></div>
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<span style="font-kerning: none" class="">In conjunction withTwenty- sixth International Joint Conference on Artificial Intelligence (IJCAI-17), August 19–20, 2017, Melbourne, Australia.</span></div>
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<span style="font-kerning: none; color: #010000" class="">Website: <a href="http://delbp.github.io/" class="">
<span style="-webkit-font-kerning: none;" class="">http://delbp.github.io</span></a></span></div>
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<span style="font-kerning: none" class="">AIM AND SCOPE </span></div>
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<span style="font-kerning: none" class="">The main goal of Declarative Learning Based Programming (DeLBP) workshop is to investigate the issues that arise when designing and using programming languages that support learning from data and knowledge.</span></div>
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<span style="font-kerning: none" class="">DeLBP aims at facilitating and simplifying the design and development of intelligent real world applications that use machine learning and reasoning by addressing the following commonly observed challenges: </span>Interaction
with messy, naturally occurring data; Specifying the requirements of the application at a high abstraction level; Dealing with uncertainty in data and knowledge in various layers of the application program; Using representations that support flexible relational
feature engineering; Using representations that support flexible reasoning and structure learning; Integrating a range of learning and inference algorithms; and finally addressing the above mentioned issues in one unified programming environment.</div>
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Conventional programming languages offer no help to application programmers that attempt to design and develop applications that make use of real world data, and reason about it in a way that involves learning interdependent concepts from data, incorporating
and composing existing models, and reasoning about existing and trained models and their parametrization. Over the last few years the research community has tried to address these problems from multiple perspectives, most notably various approaches based on
Probabilistic programming, Logical Programming and the integrated paradigms. The goal of this workshop is to present and discuss the current related research and the way various challenges have been addressed. </div>
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We aim at motivating the need for further research toward a unified framework in this area based on the key existing paradigms: Probabilistic Programming (PP), Logic Programming (LP), Probabilistic Logical Programming (PLP), First-order query languages and
database management systems (DBMS) and deductive databases (DDB), Statistical relational learning and related languages (SRL), and connect these to the ideas of Learning Based Programming. We aim to discuss and investigate the required type of languages and
representations that facilitate modeling probabilistic or non-probabilistic complex learning models, deep architectures, and provide the ability to combine, chain and perform flexible inference with existing models and by exploiting domain knowledge. (Website:
<a href="http://delbp.github.io/" class=""><span style="-webkit-font-kerning: none;" class="">http://delbp.github.io</span></a>)</div>
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<span style="font-kerning: none" class="">TOPICS OF INTEREST</span></div>
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<span style="font-kerning: none" class="">— New abstractions and modularity levels towards a unified framework for learning and reasoning,</span></div>
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<span style="font-kerning: none" class=""> ◦ Frameworks/Computational models to combine learning and reasoning paradigms and exploit accomplishments in AI from various perspectives.</span></div>
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<span style="font-kerning: none" class="">— Flexible use of structured and relational data from heterogeneous resources in learning.</span></div>
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<span style="font-kerning: none" class=""> ◦ Data modeling (relational/graph-based ) issues in such a new integrated framework for learning based on data and knowledge.</span></div>
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<span style="font-kerning: none" class="">— Exploiting knowledge such as expert knowledge and common sense knowledge expressed via multiple formalisms, in learning.</span></div>
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<span style="font-kerning: none" class="">— The ability of closing the loop to acquire knowledge from data and data from knowledge towards life-long learning, and reasoning.</span></div>
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<span style="font-kerning: none" class="">— Using declarative domain knowledge to guide the design of learning models,</span></div>
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<span style="font-kerning: none" class=""> ◦ Including feature extraction, model selection, dependency structure and deep learning architecture.</span></div>
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<span style="font-kerning: none" class="">— Structure Learning and automation of hyper-parameter tuning.</span></div>
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<span style="font-kerning: none" class="">— Design and representation of complex learning and inference models.</span></div>
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<span style="font-kerning: none" class="">— The interface for learning-based programming,</span></div>
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<span style="font-kerning: none" class=""> ◦ Either in the form of programming languages, declarations, frameworks, libraries or graphical user interfaces.</span></div>
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<span style="font-kerning: none" class="">— Storage and retrieval of trained learning models in a flexible way to facilitate incremental learning.</span></div>
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<span style="font-kerning: none" class="">— Related applications in Natural language processing, Computer vision, Bioinformatics, Computational biology, etc.</span></div>
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<span style="font-kerning: none" class="">IMPORTANT DATES</span></div>
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<span style="font-kerning: none" class="">• Submission Deadline: May 8th, 2017</span></div>
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<span style="font-kerning: none" class="">• Notification: June 5th, 2017</span></div>
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<span style="font-kerning: none" class="">• Workshop Days: August 19th-20th, 2017</span></div>
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<span style="font-kerning: none" class="">We encourage contributions with either a technical paper (IJCAI style, 6 pages without references), a position statement (IJCAI style, 2 pages maximum) or an abstract of a published work. IJCAI Style files available
<a href="http://ijcai-17.org/FormattingGuidelinesIJCAI-17.zip" class=""><span style="font-kerning: none; color: #1e6bb8" class="">here</span></a></span><span style="font-kerning: none; color: #1e6bb8" class=""> [<a href="http://ijcai-17.org/FormattingGuidelinesIJCAI-17.zip" class="">http://ijcai-17.org/FormattingGuidelinesIJCAI-17.zip</a>]</span><span style="font-kerning: none" class="">.
Please make submissions via EasyChair, <a href="https://easychair.org/conferences/?conf=delbp2017" class="">
<span style="font-kerning: none; color: #1e6bb8" class="">here</span></a></span><span style="font-kerning: none; color: #1e6bb8" class=""> [<a href="https://easychair.org/conferences/?conf=delbp2017" class="">https://easychair.org/conferences/?conf=delbp2017</a>]</span><span style="font-kerning: none" class="">.</span></div>
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<span style="font-kerning: none" class="">PROGRAM COMMITTEE </span></div>
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<span style="font-kerning: none" class=""> <a href="http://people.cs.kuleuven.be/%7Eguy.vandenbroeck/" class=""><span style="-webkit-font-kerning: none;" class="">Guy Van den Broeck</span></a>, University of California, Los Angeles</span></div>
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<span style="font-kerning: none" class=""> <a href="http://sameersingh.org/" class=""><span style="-webkit-font-kerning: none;" class="">Sameer Singh</span></a>, University of California, Irvine</span></div>
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<span style="font-kerning: none" class=""> <a href="http://www.gelberpfeffer.net/avi" class=""><span style="-webkit-font-kerning: none;" class="">Avi Pfeffer</span></a>, Charles River Analytics</span></div>
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<span style="font-kerning: none; color: #010000" class=""> <a href="http://www.ai.sri.com/%7Ebraz/" class=""><span style="-webkit-font-kerning: none;" class="">Rodrigo de Salvo Braz</span></a>, SRI International</span></div>
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<span style="font-kerning: none" class=""> <a href="https://people.cs.kuleuven.be/~tias.guns/" class="">Tias Guns</a>, Vrije University of Brussels</span></div>
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<span style="font-kerning: none" class=""> <a href="http://christos-c.com" class="">Christos Christodoulopoulos</a>, Amazon Cambridge, UK</span></div>
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<span style="font-kerning: none" class=""> <a href="https://www.cs.ucsb.edu/~william/" class="">William Wang</a>, University of California, Santa Barbara</span></div>
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<span style="font-kerning: none" class=""> <a href="http://www.cs.virginia.edu/~kc2wc/" class="">Kai-Wei Chang</a>, University of Virginia </span></div>
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<span style="font-kerning: none" class="">ORGANIZING COMMITTEE </span></div>
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<span style="text-decoration: underline ; font-kerning: none; color: #0069d9" class=""><a href="http://people.cs.kuleuven.be/%7Eparisa.kordjamshidi/" class="">Parisa Kordjamshidi</a>,</span><span style="font-kerning: none" class=""> Tulane University, IHMC</span></div>
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<span style="font-kerning: none" class=""><a href="http://l2r.cs.uiuc.edu/" class=""><span style="-webkit-font-kerning: none;" class="">Dan Roth</span></a></span><span style="text-decoration: underline ; font-kerning: none; color: #0069d9" class="">,</span><span style="font-kerning: none" class="">
University of Illinois at Urbana-Champaign</span></div>
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<span style="font-kerning: none" class=""><a href="http://www.ccs.neu.edu/home/jwvdm/" class="">Jan-Willem Van den Meent</a>, Northeastern University</span></div>
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<span style="font-kerning: none" class=""><a href="https://www.cs.purdue.edu/homes/dgoldwas/" class="">Dan Goldwasser</a>, Purdue University</span></div>
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<span style="font-kerning: none" class=""><a href="http://www.hlt.utdallas.edu/~vgogate/" class="">Vibhav Gogate</a>, University of Texas at Dallas</span></div>
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<span style="font-kerning: none" class=""><a href="http://www-ai.cs.uni-dortmund.de/PERSONAL/kersting.html" class="">Kristian Kersting</a>, TU Dortmund University</span></div>
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<span style="font-kerning: none" class="">CONTACT </span></div>
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<span style="text-decoration: underline ; font-kerning: none; color: #0069d9" class=""><a href="mailto:delbp-2@googlegroups.com" class="">delbp-2@googlegroups.com</a></span><span style="font-kerning: none" class=""> (Organization Committee)</span></div>
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<span style="text-decoration: underline ; font-kerning: none" class=""><a href="mailto:pkordjam@tulane.edu" class="">pkordjam@tulane.edu</a></span></div>
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<span style="font-kerning: none" class="">Please circulate this CFP among your colleagues and students.</span></div>
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Kordjamshidi, Parisa<br class="">
Assistant Professor <br class="">
CS Department at Tulane University
<div class="">Research Scientist at <a href="https://www.ihmc.us/" class="">IHMC</a> </div>
<div class=""><a href="http://www.cs.tulane.edu/~pkordjam/" class="">Homepage</a><br class="">
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