Optimizing Data Acquisition to Enhance Machine Learning Performance

Summary: Introduces IAS, an online clustering-based acquisition method that incrementally updates the target model (avoiding full retraining) and uses adaptive scores to balance exploration vs. exploitation when selecting clusters. Extends to IAS-AMS which picks adaptive mini-batches from multiple clusters to remove single-cluster bias; IAS gives best efficiency while IAS-AMS yields superior labeling effectiveness with runtime comparable to CTS. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13564
Venue: VLDB
Year: 2024
Pagerank: 5.7217787e-05
Overall Rank: 7,034 | 51.75%
DOI: 10.14778/3648160.3648172

Incoming Non-self Citations Over Time

Authors

1. Tingting Wang (RMIT University)
2. Shixun Huang (University of Wollongong)
3. Zhifeng Bao (RMIT University)
4. J. Shane Culpepper (University of Queensland)
5. Volkan Dedeoglu (Data61)
6. Reza Arablouei (Data61)

BibTeX Citation

@article{wang_vldb24,
        title = {{Optimizing Data Acquisition to Enhance Machine Learning Performance}},
        author = {Wang, Tingting and Huang, Shixun and Bao, Zhifeng and Culpepper, J. Shane and Dedeoglu, Volkan and Arablouei, Reza},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {6},
        pages = {1310--1323},
        doi = {10.14778/3648160.3648172},
        url = {https://doi.org/10.14778/3648160.3648172},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,541	Shapley Value Estimation Based on Differential Matrix	2025	SIGMOD	5.2528121e-05
10,198	ASSS: Adaptive Stratified Sampling for Shapley-like Values	2026	SIGMOD	5.093636e-05
10,214	CoShap: A Scalable Coalition Growth Approach to Shapley Value Approximation	2026	SIGMOD	5.093636e-05
10,746	A Cost-Effective LLM-based Approach to Identify Wildlife Trafficking in Online Marketplaces	2025	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
764	To Join or Not to Join? Thinking Twice about Joins before Feature Selection	2016	SIGMOD	0.00014226652
1,066	Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms	2019	VLDB	0.00012333161
1,121	ARDA: Automatic Relational Data Augmentation for Machine Learning	2020	VLDB	0.00012093059
2,994	Data Acquisition for Improving Machine Learning Models	2021	VLDB	7.8762343e-05
3,886	GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data	2023	SIGMOD	7.0460597e-05
4,808	Selective Data Acquisition in the Wild for Model Charging	2022	VLDB	6.4991553e-05
4,809	Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks	2021	SIGMOD	6.4984309e-05
5,510	Responsible Data Integration: Next-generation Challenges	2022	SIGMOD	6.1919207e-05
6,074	Automatic Data Acquisition for Deep Learning	2021	VLDB	5.9860133e-05
6,551	Efficient Sampling Approaches to Shapley Value Approximation	2023	SIGMOD	5.8429222e-05
7,112	Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning	2023	VLDB	5.6990782e-05

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