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Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads

Summary: ease.ml: declarative ML service for multi-tenant clusters; formalizes multi-tenant model selection to minimize global regret, balancing efficiency and fairness. A hybrid algorithm fusing bandits with Bayesian optimization (regret bound) yields up to 9.8x faster global accuracy than heuristics and 4.1x vs SOTA on synthetic data and DL/Azure ML Studio tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11769
Venue
VLDB
Year
2018
Pagerank
0.0001223506
Overall Rank
1,391 | 90.33%
DOI
10.1145/3177732.3177737

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Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank Citing Paper Year Venue Pagerank
921 Democratizing Data Science through Interactive Curation of ML Pipelines 2019 SIGMOD 0.00015337438
1,350 Northstar: An Interactive Data Science System 2018 VLDB 0.00012431059
2,384 Oracle AutoML: A Fast and Predictive AutoML Pipeline 2020 VLDB 8.925354e-05
2,839 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 8.0378978e-05
4,456 AutoOD: Automatic Outlier Detection 2023 SIGMOD 6.1704203e-05
4,748 Rafiki: Machine Learning as an Analytics Service System 2019 VLDB 5.9526539e-05
7,138 Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization 2019 VLDB 4.8216981e-05
7,420 MLBench: Benchmarking Machine Learning Services Against Human Experts 2018 VLDB 4.7347751e-05
7,494 SubStrat: A Subset-Based Optimization Strategy for Faster AutoML 2023 VLDB 4.7180617e-05
8,092 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 4.587921e-05
8,182 SHiFT: An Efficient, Flexible Search Engine for Transfer Learning 2023 VLDB 4.5659133e-05
8,828 HAIPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation 2023 SIGMOD 4.4407488e-05
9,117 Ease.ml in Action: Towards Multi-tenant Declarative Learning Services 2018 VLDB 4.3928617e-05
9,222 Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning 2021 VLDB 4.3698672e-05
11,431 Ease.ML: A Lifecycle Management System for MLDev and MLOps 2021 CIDR 4.1945683e-05
11,607 Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development 2020 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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