A Cost-based Optimizer for Gradient Descent Optimization

Summary: Cost-based optimizer for gradient-descent plans in declarative ML tasks. Introduces abstract GD operators and a convergence-iteration estimator to enable plan selection and optimizations that yield orders-of-magnitude speedups on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5480
Venue: SIGMOD
Year: 2017
Pagerank: 5.7287645e-05
Overall Rank: 7,000 | 51.98%
DOI: 10.1145/3035918.3064042

Incoming Non-self Citations Over Time

Authors

1. Zoi Kaoudi (Hamad Bin Khalifa University; Qatar Computing Research Institute)
2. Jorge-Arnulfo Quiané-Ruiz (Hamad Bin Khalifa University; Qatar Computing Research Institute)
3. Saravanan Thirumuruganathan (Hamad Bin Khalifa University; Qatar Computing Research Institute)
4. Sanjay Chawla (Hamad Bin Khalifa University; Qatar Computing Research Institute)
5. Divy Agrawal (University of California Santa Barbara)

BibTeX Citation

@inproceedings{kaoudi_sigmod17,
        title = {{A Cost-based Optimizer for Gradient Descent Optimization}},
        author = {Kaoudi, Zoi and Quiané-Ruiz, Jorge-Arnulfo and Thirumuruganathan, Saravanan and Chawla, Sanjay and Agrawal, Divy},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3064042},
        url = {https://dl.acm.org/doi/10.1145/3035918.3064042},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,169	Towards Demystifying Serverless Machine Learning Training	2021	SIGMOD	7.6715222e-05
3,351	RHEEM: Enabling Cross-Platform Data Processing - May The Big Data Be With You! -	2018	VLDB	7.4937347e-05
6,038	Efficient Construction of Approximate Ad-Hoc ML models Through Materialization and Reuse	2018	VLDB	5.9990929e-05
6,485	Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent	2019	SIGMOD	5.8657457e-05
9,076	Leveraging Similarity Joins for Signal Reconstruction	2018	VLDB	5.3251649e-05
9,620	Apache Wayang in Action: Enabling Data Systems Integration via a Unified Data Analytics Framework	2025	SIGMOD	5.2434488e-05
9,742	Unified Data Analytics: State-of-the-art and Open Problems	2022	VLDB	5.227679e-05
11,674	Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study	2021	SIGMOD	5.093636e-05
11,681	Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions	2021	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
106	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033539462
415	SystemML: Declarative Machine Learning on Spark	2016	VLDB	0.0001888524
518	Towards a Unified Architecture for in-RDBMS Analytics	2012	SIGMOD	0.00017167492
532	MLbase: A Distributed Machine-learning System	2013	CIDR	0.00017072641
579	Incremental Knowledge Base Construction Using DeepDive	2015	VLDB	0.00016217563
640	Materialization Optimizations for Feature Selection Workloads	2014	SIGMOD	0.00015409494
715	Learning Generalized Linear Models Over Normalized Data	2015	SIGMOD	0.00014655327
1,079	Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML	2014	VLDB	0.00012258469
1,150	DimmWitted: A Study of Main-Memory Statistical Analytics	2014	VLDB	0.00011943462
2,217	Cumulon: Optimizing Statistical Data Analysis in the Cloud	2013	SIGMOD	8.9332438e-05
9,983	Rheem: Enabling Multi-Platform Task Execution	2016	SIGMOD	5.1844786e-05

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