ML Systems Workshop
A new area is emerging at the intersection of artificial intelligence, machine learning, and systems design. This birth is driven by the explosive growth of diverse applications of ML in production, the continued growth in data volume, and the complexity of large-scale learning systems. The goal of this workshop is to bring together experts working at the crossroads of machine learning, system design and software engineering to explore the challenges faced when building practical large-scale ML systems. In particular, we aim to elicit new connections among these diverse fields, and identify tools, best practices and design principles. We also want to think about how to do research in this area and properly evaluate it. The workshop will cover ML and AI platforms and algorithm toolkits, as well as dive into machine learning-focused developments in distributed learning platforms, programming languages, data structures, GPU processing, and other topics.
Call for Papers
We invite participation in the ML Systems Workshop which will be held in conjunction with NIPS 2017 on December 8, 2017 in Long Beach, California.
- Submission Deadline: EXTENDED October 25, 2017
- Author Notification Deadline: EXTENDED November 9, 2017
- Submission Details: Submissions can be up to 6 pages (not including references) and do not have to be anonymized. All submissions must be in PDF format and should follow the NIPS 2017 format: https://nips.cc/Conferences/2017/PaperInformation/StyleFiles.
- Sarah Bird, Facebook Research email@example.com
- Dan Crankshaw, UC Berkeley firstname.lastname@example.org
- Garth Gibson, CMU and Vector Institute, email@example.com
- Joseph Gonzalez, UC Berkeley, firstname.lastname@example.org
- Aparna Lakshmiratan, Facebook, email@example.com
- Li Erran Li, Uber, firstname.lastname@example.org
- Christopher Re, Stanford, email@example.com
- Siddhartha Sen, Microsoft Research, firstname.lastname@example.org