Efficient Construction of Approximate Ad-Hoc ML models Through Materialization and Reuse

Summary: Proposes materialization and reuse of previously built ML models to answer new analytic queries over OLAP-aligned data. A cost-based framework selects and composes models (GLMs, K-Means, GMM) to approximate new queries, yielding large speedups on big data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h0831fa94e7fe8eaa
Venue: VLDB
Year: 2018
Pagerank: 5.8721471e-05
Overall Rank: 6,143 | 58.70%
DOI: 10.14778/3236187.3236199

Incoming Non-self Citations Over Time

Authors

1. Sona Hasani (University of Texas)
2. Saravanan Thirumuruganathan (Hamad Bin Khalifa University; Qatar Computing Research Institute; University of Texas)
3. Abolfazl Asudeh (University of Michigan)
4. Nick Koudas (University of Toronto)
5. Gautam Das (University of Texas)

BibTeX Citation

@article{hasani_vldb18,
        title = {{Efficient Construction of Approximate Ad-Hoc ML models Through Materialization and Reuse}},
        author = {Hasani, Sona and Thirumuruganathan, Saravanan and Asudeh, Abolfazl and Koudas, Nick and Das, Gautam},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {11},
        pages = {1468--1481},
        doi = {10.14778/3236187.3236199},
        url = {https://doi.org/10.14778/3236187.3236199},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,969	Optimizing Machine Learning Inference Queries with Correlative Proxy Models	2022	VLDB	6.8899861e-05
4,195	PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models	2020	SIGMOD	6.7422305e-05
6,217	Materialization and Reuse Optimizations for Production Data Science Pipelines	2022	SIGMOD	5.8474357e-05
8,807	ApproxML: Efficient Approximate Ad-Hoc ML Models Through Materialization and Reuse	2019	VLDB	5.2728127e-05
11,264	Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching	2025	VLDB	4.9793485e-05
11,988	Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions	2021	SIGMOD	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
105	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033638251
138	Join Synopses for Approximate Query Answering	1999	SIGMOD	0.00029627449
372	Approximate Query Processing: Taming the TeraBytes! A Tutorial	2001	VLDB	0.00019720059
509	Goods: Organizing Google's Datasets	2016	SIGMOD	0.00017071087
654	Materialization Optimizations for Feature Selection Workloads	2014	SIGMOD	0.0001510357
730	Learning Generalized Linear Models Over Normalized Data	2015	SIGMOD	0.00014406936
777	To Join or Not to Join? Thinking Twice about Joins before Feature Selection	2016	SIGMOD	0.00014054709
931	Dynamic Sample Selection for Approximate Query Processing	2003	SIGMOD	0.00013011667
1,255	Data Management in Machine Learning: Challenges, Techniques, and Systems	2017	SIGMOD	0.00011325762
1,691	MISTIQUE: A System to Store and Query Model Intermediates for Model Diagnosis	2018	SIGMOD	9.8570722e-05
3,524	MLog: Towards Declarative In-Database Machine Learning	2017	VLDB	7.2337006e-05
6,076	Mining Multi-Dimensional Constrained Gradients in Data Cubes	2001	VLDB	5.8940835e-05
6,543	Prediction Cubes	2005	VLDB	5.7519742e-05
7,142	A Cost-based Optimizer for Gradient Descent Optimization	2017	SIGMOD	5.600563e-05
8,295	NetCube: A Scalable Tool for Fast Data Mining and Compression	2001	VLDB	5.3612406e-05

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