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GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data
Summary: GoodCore selects a coreset for incomplete data by modeling missingness as repairs over worlds and optimizing the expected subset without cleaning. It proves NP-hard and offers an approximation with imputation-based variants, enabling data-efficient ML.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6661
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 6.4460899e-05
- Overall Rank
- 4,103 | 71.49%
- DOI
-
10.1145/3589302
Incoming Non-self Citations Over Time
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| 8,121 |
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| 9,708 |
Outlier Summarization via Human Interpretable Rules |
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VLDB |
4.2951473e-05 |
| 10,239 |
BRIEF: Bi-level Coreset Selection for Efficient Instruction Tuning in LLMs |
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4.1905499e-05 |
| 10,301 |
LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning |
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4.1905499e-05 |
| 10,537 |
Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection |
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4.1905499e-05 |
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| 10,816 |
DemandClean: A Multi-Objective Learning Framework for Balancing Model Tolerance to Data Authenticity and Diversity |
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VLDB |
4.1905499e-05 |
| 10,956 |
Certain and Approximately Certain Models for Statistical Learning |
2024 |
SIGMOD |
4.1905499e-05 |
| 11,003 |
MisDetect: Iterative Mislabel Detection using Early Loss |
2024 |
VLDB |
4.1905499e-05 |
| 11,044 |
QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models |
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VLDB |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 49 |
Consistent Query Answers in Inconsistent Databases |
1999 |
PODS |
0.00067607389 |
| 656 |
ERACER: A Database Approach for Statistical Inference and Data Cleaning |
2010 |
SIGMOD |
0.00018590675 |
| 788 |
ActiveClean: Interactive Data Cleaning For Statistical Modeling |
2016 |
VLDB |
0.00016618698 |
| 2,308 |
Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions |
2021 |
VLDB |
9.0634287e-05 |
| 2,574 |
Database Repairs and Consistent Query Answering: Origins and Further Developments |
2019 |
PODS |
8.5126812e-05 |
| 3,313 |
Efficient and Effective Data Imputation with Influence Functions |
2022 |
VLDB |
7.2336734e-05 |
| 4,829 |
Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks |
2021 |
SIGMOD |
5.8890126e-05 |
| 5,026 |
Adaptive Data Augmentation for Supervised Learning over Missing Data |
2021 |
VLDB |
5.7451454e-05 |
| 5,254 |
CDB: A Crowd-Powered Database System |
2018 |
VLDB |
5.5991922e-05 |
| 5,369 |
Cost-Effective Crowdsourced Entity Resolution: A Partial-Order Approach |
2016 |
SIGMOD |
5.5436995e-05 |
| 5,386 |
Selective Data Acquisition in the Wild for Model Charging |
2022 |
VLDB |
5.5346315e-05 |
| 5,965 |
Automatic Data Acquisition for Deep Learning |
2021 |
VLDB |
5.2476363e-05 |
| 7,180 |
Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning |
2023 |
VLDB |
4.8032775e-05 |
| 7,580 |
Human-in-the-loop Outlier Detection |
2020 |
SIGMOD |
4.7023767e-05 |
| 9,224 |
VisClean: Interactive Cleaning for Progressive Visualization |
2020 |
VLDB |
4.3657563e-05 |
| 11,586 |
Interactively Discovering and Ranking Desired Tuples without Writing SQL Queries |
2020 |
SIGMOD |
4.1905499e-05 |
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