Automatic Data Acquisition for Deep Learning
Summary: AutoData, an RL-guided system, automatically acquires training data from open ML benchmarks and data markets to support DL training. Its policy learns from AutoML feedback to guide high-quality data search; demonstrated on image classification and relational data prediction. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiabin Liu (Tsinghua University)
- 2. Fu Zhu (Tsinghua University)
- 3. Chengliang Chai (Tsinghua University)
- 4. Yuyu Luo (Tsinghua University)
- 5. Nan Tang (Qatar Computing Research Institute)
BibTeX Citation
@article{liu_vldb21,
title = {{Automatic Data Acquisition for Deep Learning}},
author = {Liu, Jiabin and Zhu, Fu and Chai, Chengliang and Luo, Yuyu and Tang, Nan},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2739--2742},
doi = {10.14778/3476311.3476333},
url = {https://doi.org/10.14778/3476311.3476333},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,942 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.9105312e-05 |
| 4,869 | Selective Data Acquisition in the Wild for Model Charging | 2022 | VLDB | 6.3719187e-05 |
| 5,610 | Responsible Data Integration: Next-generation Challenges | 2022 | SIGMOD | 6.0660772e-05 |
| 5,748 | Optimizing Data Acquisition to Enhance Machine Learning Performance | 2024 | VLDB | 6.0054988e-05 |
| 7,203 | Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning | 2023 | VLDB | 5.5845207e-05 |
| 7,262 | Learned Data-aware Image Representations of Line Charts for Similarity Search | 2023 | SIGMOD | 5.5694763e-05 |
| 11,070 | LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning | 2026 | VLDB | 4.9769913e-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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 205 | Snorkel: Rapid Training Data Creation with Weak Supervision | 2018 | VLDB | 0.00025171314 |
| 765 | Table Union Search on Open Data | 2018 | VLDB | 0.00014119196 |
| 1,336 | Auctus: A Dataset Search Engine for Data Discovery and Augmentation | 2021 | VLDB | 0.00010984121 |
| 4,625 | Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach | 2016 | SIGMOD | 6.4948389e-05 |
| 4,865 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 6.3740341e-05 |
| 7,043 | Human-in-the-loop Outlier Detection | 2020 | SIGMOD | 5.611642e-05 |
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