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.
Now in its second edition, the workshop on Machine Learning and Programming Languages (MAPL) will be a forum for researchers from both programming systems and machine learning to discuss recent developments in both research communities, and how researchers from both communities can leverage such advances in conducive and innovative ways.
MAPL will take place at PLDI this year on Monday, June 18 2018. The call for papers is now available.
Mon 18 JunDisplayed time zone: Eastern Time (US & Canada) change
09:15 - 09:30 | IntroductionMAPL at Columbus Ballroom A Chair(s): Alvin Cheung University of Washington, Justin Gottschlich Intel Labs | ||
09:30 - 10:30 | |||
09:30 30mTalk | Ariadne: Analysis for Machine Learning Programs MAPL Julian Dolby IBM Thomas J. Watson Research Center, Avraham Shinnar IBM Research, Allison Allain IBM Research, Jenna Reinen IBM Research | ||
10:00 30mTalk | Clone-Hunter: Accelerated Bound Checks Elimination via Binary Code Clone Detection MAPL Hongfa Xue George Washington University, Guru Venkataramani George Washington University, Tian Lan George Washington University |
11:00 - 12:00 | |||
11:00 30mTalk | Obfuscation Resilient Search through Executable Classification MAPL Fang-Hsiang Su Columbia University, New York, Jonathan Bell George Mason University, Gail Kaiser Columbia University, New York, Baishakhi Ray Columbia University, New York | ||
11:30 30mTalk | Retrieval on source code: a neural code search MAPL Saksham Sachdev Facebook, Hongyu Li Rice University, Sifei Luan Facebook, Seohyun Kim Facebook, Koushik Sen University of California, Berkeley, Satish Chandra Facebook |
14:00 - 15:30 | |||
14:00 30mTalk | Relay: A New IR for Machine Learning Frameworks MAPL Jared Roesch University of Washington, USA, Steven Lyubomirsky University of Washington, USA, Logan Weber University of Washington, Josh Pollock University of Washington, Marisa Kirisame , Tianqi Chen , Zachary Tatlock University of Washington, Seattle | ||
14:30 30mTalk | Diesel - DSL for Linear Algebra and Neural Net Computations on GPUs MAPL Venmugil Elango NVIDIA, Norm Rubin NVIDIA, Mahesh Ravishankar , Hari Sandanagobalane NVIDIA, Vinod Grover | ||
15:00 30mTalk | Gen: probabilistic programming with fast custom inference via code generation MAPL File Attached |
16:10 - 16:40 | |||
16:10 30mTalk | The Three Pillars of Machine Programming MAPL Justin Gottschlich Intel Labs, Armando Solar-Lezama MIT CSAIL, Nesime Tatbul Intel Labs and MIT, Michael Carbin MIT, Martin C. Rinard Massachusetts Institute of Technology, Regina Barzilay MIT, Saman Amarasinghe MIT, Joshua B. Tenenbaum MIT, Tim Mattson Intel, USA |
16:40 - 17:00 | Closing RemarksMAPL at Columbus Ballroom A Chair(s): Alvin Cheung University of Washington, Justin Gottschlich Intel Labs | ||
17:00 - 18:00 | |||
Accepted Papers
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.
This workshop seeks to bring together programming language and machine learning communities to encourage collaboration and exploration in the areas of mutual benefit. The workshop will include a combination of peer-reviewed papers and invited events. The workshop will seek papers on a diverse range of topics related to programming languages and machine learning including (and not limited to):
- Application of machine learning to compilation and run-time scheduling
- Collaborative human / computer programming
- Inductive programming
- Infrastructure and techniques for mining and analyzing large code bases
- Interoperability between machine learning frameworks and existing code bases
- Probabilistic programming
- Programming language and compiler support for machine learning applications
- Programming language support and implementation of deep learning frameworks
Evaluation Criteria
As in previous year, reviewers will evaluate each contribution for its significance, originality, and clarity to the topics listed above. Submissions should clearly state how their novelty and how they improve upon existing work.
This year we will be using double-blind reviewing. This means that author names and affiliations must be omitted from the submission. Additionally, if the submission refers to prior work done by the authors, that reference should be made in third person. These are firm submission requirements. If you have questions about making your paper double blind, please contact the Program Chair.
Paper Submissions
Submissions must be in English. papers should be in PDF and format and no more than 8 pages in standard two-column SIGPLAN conference format including figures and tables but excluding 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 online submission site.
All accepted papers will appear in the published proceedings and available on the ACM Digital Library. Authors will have the option of having their final paper accessible from the workshop website as well.
Authors must be familiar with and abide by SIGPLAN’s republication policy, which forbids simultaneous submission to multiple venues and requires disclosing prior publication of closely related work.
Posters
Besides papers, MAPL this year will also have a poster session. We invite poster submissions that are related to the workshop topics. For each poster, please prepare a maximum 1 page abstract summarizing your project. All reasonable posters will be accepted. The poster titles will be posted on the workshop website but will not be included as part of the official proceedings, hence authors will be able to submit their work as a full paper to other venues. See below for submission deadlines. Note that posters should be submitted to a separate website. Use the ACM standard two-column SIGPLAN conference format for your poster abstract.
Important Dates
Papers
- Submission deadline:
Wednesday, Feb 28 2018Friday, March 9 2018 (11:59pm Pacific Time) - Author notification: Monday, April 9 2018
- Camera-ready deadline: Monday, May 7 2018
Posters
- Poster submission deadline: Friday, May 18, 2018 (11:59pm Pacific Time)
- Author notification for posters: June 1, 2018
Workshop: Monday, June 18 2018