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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)

Paper ID
5887
Venue
SIGMOD
Year
2020
Pagerank
9.3953268e-05
Overall Rank
2,164 | 84.97%
DOI
10.1145/3318464.3386126

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 18 of 18 citing papers.

Rank Citing Paper Year Venue Pagerank
1,942 SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging 2021 SIGMOD 0.00010010569
2,456 Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities 2021 SIGMOD 8.7649259e-05
2,845 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 8.0301674e-05
4,054 Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees 2023 SIGMOD 6.4910804e-05
4,779 LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems 2021 SIGMOD 5.9259373e-05
4,799 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 5.9082876e-05
6,735 Hindsight Logging for Model Training 2021 VLDB 4.9420202e-05
7,493 SubStrat: A Subset-Based Optimization Strategy for Faster AutoML 2023 VLDB 4.7135369e-05
8,150 Cloud Databases: New Techniques, Challenges, and Opportunities 2022 VLDB 4.5714701e-05
8,888 COSMO: A Large-Scale E-commerce Common Sense Knowledge Generation and Serving System at Amazon 2024 SIGMOD 4.4236765e-05
9,116 Towards Observability for Production Machine Learning Pipelines 2022 VLDB 4.3886184e-05
9,215 PACE: Poisoning Attacks on Learned Cardinality Estimation 2024 SIGMOD 4.3679174e-05
9,732 ContTune: Continuous Tuning by Conservative Bayesian Optimization for Distributed Stream Data Processing Systems 2023 VLDB 4.2901665e-05
10,350 Flow with FlorDB: Incremental Context Maintenance for the Machine Learning Lifecycle 2025 CIDR 4.1905499e-05
11,080 A Flexible Forecasting Stack 2024 VLDB 4.1905499e-05
11,221 F3 KM: Federated, Fair, and Fast k-means 2023 SIGMOD 4.1905499e-05
11,315 Towards Observability for Machine Learning Pipelines 2022 CIDR 4.1905499e-05
11,391 CDI-E: An Elastic Cloud Service for Data Engineering 2022 VLDB 4.1905499e-05
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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
39 Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud 2012 VLDB 0.00075263552
557 SystemML: Declarative Machine Learning on Spark 2016 VLDB 0.00020186115
1,044 DimmWitted: A Study of Main-Memory Statistical Analytics 2014 VLDB 0.00014465007
1,793 Summingbird: A Framework for Integrating Batch and Online MapReduce Computations 2014 VLDB 0.00010522029
2,122 SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle 2020 CIDR 9.4905306e-05
2,146 Scalable K-Means++ 2012 VLDB 9.4341455e-05
5,265 Probabilistic Demand Forecasting at Scale 2017 VLDB 5.5950627e-05
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