Name
Abstract | ||
|---|---|---|
Continuous integration (CI) has been a de facto standard for building industrial-strength software. Yet, there is little attention towards applying CI to the development of machine learning (ML) applications until the very recent effort on the theoretical side. In this paper, we take a step forward to bring the theory into practice.
We develop the first CI system for ML, to the best of our knowledge, that integrates seamlessly with existing ML development tools. We present its design and implementation details.
|
Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3394486.3403290 | KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Virtual Event
CA
USA
July, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7998-4 | 1 |
PageRank | References | Authors |
0.36 | 7 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bojan Karlas | 1 | 9 | 5.05 |
| Matteo Interlandi | 2 | 182 | 24.28 |
| Cèdric Renggli | 3 | 9 | 4.23 |
| Wentao Wu | 4 | 394 | 30.53 |
| Ce Zhang | 5 | 803 | 83.39 |
| Deepak Mukunthu Iyappan Babu | 6 | 1 | 0.36 |
| Jordan Edwards | 7 | 1 | 0.36 |
| Chris Lauren | 8 | 1 | 0.36 |
| Andy Xu | 9 | 1 | 0.36 |
| Markus Weimer | 10 | 827 | 50.86 |