[TYPES/announce] Call for Papers: ACM SIGPLAN Workshop on Machine Learning and Programming Languages 2018

Alvin Cheung akcheung at cs.washington.edu
Sun Jan 28 19:52:01 EST 2018


ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL)

http://pldi18.sigplan.org/track/mapl-2018-papers

To be held in conjunction with PLDI 2018 in Philadelphia, USA

Now in its second edition, MAPL is a forum for researchers to discuss 
new advances in programming systems and machine learning, and to 
encourage collaboration and exploration in the areas of mutual benefit.

*Call for Papers*
The workshop seeks papers on a diverse range of topics related to 
programming languages and machine learning including (and not limited to):
- Programming language and compiler support for machine learning 
applications
- Programming language support and implementation of deep learning 
frameworks
- Inductive programming
- Probabilistic programming
- Application of machine learning to compilation and run-time scheduling
- Collaborative human / computer programming
- Interoperability between machine learning frameworks and existing code 
bases 

- Infrastructure and techniques for mining and analyzing large code bases

*Important Dates*
Paper submission: Wed Feb 28 2018
Author notification: Mon April 2 2018
Camera-ready Deadline: Fri May 4 2018
(all times are 5pm Pacific Standard Time)

If you have any questions, please feel free to contact the program chair.

On behalf of our organizational committee:
Alvin Cheung, University of Washington, USA (Program Chair)
Justin Gottschlich, Intel Labs, USA (General Chair)
Tatiana Shpeisman, Google, USA (Steering Committee Chair)

the following program committee members:
Premkumar Devanbu, University of California at Davis, USA
Jian-Guang Lou, Microsoft Research Asia, China
Abdullah Muzahid, University of Texas at San Antonio, USA
Sebastian Riedel, University College London, UK
Tatiana Shpeisman, Google, USA
Rishabh Singh, Microsoft Research, USA
Armando Solar-Lezama, Massachusetts Institute of Technology, USA
Dawn Song, University of California at Berkeley, USA
Charles Sutton, University of Edinburgh, UK
Nesime Tatbul, Intel Labs, USA
Martin Vechev, ETH Zurich, Switzerland
Tao Xie, University of Illinois at Urbana-Champaign, USA
Eran Yahav, Technion, Israel

and the following steering committee members:
Rajkishore Barik, Intel Labs, USA
Stefano Ermon, Stanford University, USA
Costin Iancu, Lawrence Berkeley National Laboratory, USA
Kunle Olukotun, Stanford University, USA


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