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

(co-located with PLDI 2017)

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


Submissions

MAPL paper submissions should be made through EasyChair.

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. Submissions must be made through the on-line submission site. Formal proceedings will be included in the ACM digital archive and available at the workshop.


Registration and Workshop Information

Registration information coming soon.


Important Dates (tentative):

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


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)