Elastic Machine Learning Algorithms in Amazon SageMaker
Summary: Elastic training on SageMaker with incremental, resumable, elastic learning and hyperparameter optimization. Adaptation of common ML algorithms to SageMaker; experiments show faster, cheaper training vs JVM-based implementations on datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Edo Liberty
- 2. Zohar Karnin
- 3. Bing Xiang
- 4. Laurence Rouesnel
- 5. Baris Coskun
- 6. Ramesh Nallapati
- 7. Julio Delgado
- 8. Amir Sadoughi
- 9. Yury Astashonok
- 10. Piali Das
- 11. Can Balioglu
- 12. Saswata Chakravarty
- 13. Madhav Jha
- 14. Philip Gautier
- 15. David Arpin
- 16. Tim Januschowski
- 17. Valentin Flunkert
- 18. Yuyang Wang
- 19. Jan Gasthaus
- 20. Lorenzo Stella
- 21. Syama Rangapuram
- 22. David Salinas
- 23. Sebastian Schelter
- 24. Alex Smola
Incoming Citations (Sorted by Pagerank)
Showing 18 of 18 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 37 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.0007522744 |
| 557 | SystemML: Declarative Machine Learning on Spark | 2016 | VLDB | 0.00020197988 |
| 1,044 | DimmWitted: A Study of Main-Memory Statistical Analytics | 2014 | VLDB | 0.00014475229 |
| 1,794 | Summingbird: A Framework for Integrating Batch and Online MapReduce Computations | 2014 | VLDB | 0.00010532024 |
| 2,093 | Scalable K-Means++ | 2012 | VLDB | 9.5588104e-05 |
| 2,122 | SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle | 2020 | CIDR | 9.4989076e-05 |
| 5,257 | Probabilistic Demand Forecasting at Scale | 2017 | VLDB | 5.6003925e-05 |
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