Smile: A System to Support Machine Learning on EEG Data at Scale
Summary: Smile combines interactive, coordinated time/frequency visualization with deep active learning for clinical EEG labeling and IIC classification. It scales exploration to 350M segments (30 TB) under 500 ms, iteratively selecting labels that most improve the model. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lei Cao (Massachusetts Institute of Technology)
- 2. Wenbo Tao (Massachusetts Institute of Technology)
- 3. Sungtae An (Georgia Institute of Technology)
- 4. Jing Jin (Massachusetts General Hospital)
- 5. Yizhou Yan (Massachusetts Institute of Technology)
- 6. Xiaoyu Liu (Massachusetts Institute of Technology)
- 7. Wendong Ge (Massachusetts General Hospital)
- 8. Adam Sah (Massachusetts Institute of Technology)
- 9. Leilani Battle (University of Maryland)
- 10. Jimeng Sun (Georgia Institute of Technology)
- 11. Remco Chang (Tufts University)
- 12. Brandon Westover (Massachusetts General Hospital)
- 13. Samuel Madden (Massachusetts Institute of Technology)
- 14. Michael Stonebraker (Massachusetts Institute of Technology)
BibTeX Citation
@article{cao_vldb19,
title = {{Smile: A System to Support Machine Learning on EEG Data at Scale}},
author = {Cao, Lei and Tao, Wenbo and An, Sungtae and Jin, Jing and Yan, Yizhou and Liu, Xiaoyu and Ge, Wendong and Sah, Adam and Battle, Leilani and Sun, Jimeng and Chang, Remco and Westover, Brandon and Madden, Samuel and Stonebraker, Michael},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {2230--2241},
doi = {10.14778/3352063.3352138},
url = {https://doi.org/10.14778/3352063.3352138},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,404 | Dagger: A Data (not code) Debugger | 2020 | CIDR | 6.2294192e-05 |
| 6,721 | Sintel: A Machine Learning Framework to Extract Insights from Signals | 2022 | SIGMOD | 5.7940977e-05 |
| 8,876 | LANCET: Labeling Complex Data at Scale | 2021 | VLDB | 5.3534114e-05 |
| 9,394 | iEDeaL: A Deep Learning Framework for Detecting Highly Imbalanced Interictal Epileptiform Discharges | 2023 | VLDB | 5.2755515e-05 |
| 11,168 | RITA: Group Attention is All You Need for Timeseries Analytics | 2024 | SIGMOD | 5.093636e-05 |
| 11,789 | TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications | 2020 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 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 | 0.00025235185 |
| 410 | SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics | 2015 | VLDB | 0.0001890421 |
| 1,094 | Snuba: Automating Weak Supervision to Label Training Data | 2019 | VLDB | 0.00012214617 |
| 1,585 | Dynamic Prefetching of Data Tiles for Interactive Visualization | 2016 | SIGMOD | 0.00010288399 |
| 1,634 | Rapid Sampling for Visualizations with Ordering Guarantees | 2015 | VLDB | 0.00010163938 |
| 3,094 | Efficient Spatial Sampling of Large Geographical Tables | 2012 | SIGMOD | 7.765466e-05 |
| 4,926 | Adaptive Sampling for Rapidly Matching Histograms | 2018 | VLDB | 6.4428362e-05 |
| 5,737 | Kyrix: Interactive Visual Data Exploration at Scale | 2019 | CIDR | 6.1049023e-05 |
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