[TYPES/announce] MAPL Call for Papers

[Lindsey Kuper]

The First Workshop on Machine Learning and Programming Languages (MAPL)
(https://sites.google.com/view/mapl2017/home, co-located with PLDI)

Call for Papers

Due to recent algorithmic and computational advances, machine learning
has seen a surge of interest in both research and practice. From
natural language processing to self-driving cars, machine learning is
creating new possibilities that are changing the way we live and
interact with computers. However, the impact of these advances on
programming languages remains mostly untapped. Yet, incredible
research opportunities exist when combining machine learning and
programming languages in novel ways. MAPL seeks to bring together
programming language and machine learning communities to encourage
collaboration and exploration in cross disciplinary research. The
workshop will include a combination of peer-reviewed papers and
invited events, such as invited talks, panels and/or town hall
discussions.

MAPL seeks papers on a diverse range of topics related to programming
languages and machine learning including:

-        Programming languages and compilers for machine learning
-        Deep learning frameworks
-        Machine learning for compilation and run-time scheduling
-        Improving programmer productivity via machine learning
-        Inductive programming
-        Formal verification of machine learning systems
-        Probabilistic programming
-        Collaborative human / computer programming
-        Interoperability of machine learning frameworks and existing code bases

Important Dates:

-        Submission Deadline: April 3, 2017
-        Author Notification: April 24, 2017
-        Camera-ready Deadline: May 10, 2017
-        Workshop: June 18, 2017

Submissions:

Papers must be submitted in PDF and be no more than 8 pages in
standard two-column SIGPLAN conference format including figures and
tables but not including references. Shorter submissions are welcome.
The submissions will be judged based on the merit of the ideas rather
than the length. Formal proceedings will be included in the ACM
digital archive and available at the workshop.

General Chair: Tatiana Shpeisman
Program Chair: Justin Gottschlich

Program Committee:

Raj Barik (Intel Labs)
Stefano Ermon (Stanford University)
Justin Gottschlich (Program Chair, Intel Labs)
Mary Hall (University of Utah)
Peter Hawkins (Google)
Costin Iancu (Lawrence Berkeley National Lab)
Michael O’Boyle (University of Edinburgh)
Kunle Olukotun (Stanford University)
Tatiana Shpeisman (Intel Labs)

Organizing Committee:

Raj Barik (Intel Labs)
Stefano Ermon (Stanford University)
Justin Gottschlich (Intel Labs)
Costin Iancu (Lawrence Berkeley National Lab)
Kunle Olukotun (Stanford University)
Tatiana Shpeisman (Intel Labs)