PLDI 2017 Workshops
38th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2017)
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1st ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL 2017), June 18, 2017, Barcelona, Spain

MAPL 2017 – Advance Table of Contents

Contents - Abstracts - Authors

Frontmatter

Title Page
Message from the Chairs

1st ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL 2017)

Languages and Frameworks

A Computational Model for TensorFlow: An Introduction
Martín Abadi, Michael Isard, and Derek G. Murray
(Google Brain, USA)
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Dyna: Toward a Self-Optimizing Declarative Language for Machine Learning Applications
Tim Vieira, Matthew Francis-Landau, Nathaniel Wesley Filardo, Farzad Khorasani, and Jason Eisner
(Johns Hopkins University, USA; Rice University, USA)
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Debugging, Analysis, and Verification

Combining the Logical and the Probabilistic in Program Analysis
Xin Zhang, Xujie Si, and Mayur Naik
(Georgia Institute of Technology, USA; University of Pennsylvania, USA)
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Debugging Probabilistic Programs
Chandrakana Nandi, Dan Grossman, Adrian Sampson, Todd Mytkowicz, and Kathryn S. McKinley
(University of Washington, USA; Cornell University, USA; Microsoft Research, USA; Google, USA)
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Learning a Classifier for False Positive Error Reports Emitted by Static Code Analysis Tools
Ugur Koc, Parsa Saadatpanah, Jeffrey S. Foster, and Adam A. Porter
(University of Maryland at College Park, USA)
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Verified Perceptron Convergence Theorem
Charlie Murphy, Patrick Gray, and Gordon Stewart
(Princeton University, USA; Ohio University, USA)
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