Overview

Directions in Statistical Computing (DSC) 2016 was an invitation-only conference held at Stanford University July 1-2. The major themes were language design/implementation and distributed computing. Morning talks were followed by self-organizing groups and a general assembly of the R Foundation both afternoons.

Talks

July 1, 8:30-12: Languages

• Tomas Kalibera: Some Improvements of the Byte-code Compiler & Problems in Existing R/C Code [pdf]
• Viral Shah: Interfacing R and Julia [pdf]
• Doug Bates: Accessing Python, R and C++ from Julia [url]
• John Chambers: A Structure for Interfaces from R [pdf]
• Gabe Becker: Extending the C-level R Vector API [html]
• Jan Vitek: Optional typing for R: costs and benefits [pdf]
• Hadley Wickham: Non-standard and Lazy Evaluation: The lazyeval Package [pdf]
• Mikhail Arkhipov: R Tools for Visual Studio: Integration with R [pdf]

July 2, 8:30-12: Distributed computing

• Jim Hester: covr for multiple threads and child processes [pdf]
• JJ Allaire: Extensible Interfaces to Spark from R [html]
• Ryan Hafen: The Need for Flexibility in Distributed Computing with R [pdf]
• Erin LeDell: Distributed machine learning & R [pdf]
• Matt Dowle: Proposal and code for parallel sort in base R [pdf]
• Michael Kane / Bryan Lewis: Building Regression Routines on R’s Concurrent Computing Packages [pdf]
• Simon Urbanek: RCloud
• Mario Inchiosa: Scalable Data Science with Hadoop, Spark and R [pdf]