Win-Win: On Simultaneous Clustering and Imputing over Incomplete Data
Summary: Joint clustering-and-imputation formulation for incomplete data (NP-hard), showing simultaneous optimization yields mutually reinforcing gains versus impute-then-cluster. Exact ILP and practical LP-relaxation + local-neighbor (LN) approximations with guarantees; empirical wins on real datasets. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yu Sun
- 2. Jingyu Zhu
- 3. Xiao Xu
- 4. Xian Xu
- 5. Yuyao Sun
- 6. Shaoxu Song
- 7. Xiang Li
- 8. Xiaojie Yuan
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 192 | HoloClean: Holistic Data Repairs with Probabilistic Inference | 2017 | VLDB | 0.00035728858 |
| 656 | ERACER: A Database Approach for Statistical Inference and Data Cleaning | 2010 | SIGMOD | 0.00018588729 |
| 881 | Don’t be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes | 2013 | SIGMOD | 0.00015661103 |
| 2,291 | Data Generation using Declarative Constraints | 2011 | SIGMOD | 9.0926719e-05 |
| 2,302 | Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions | 2021 | VLDB | 9.0668832e-05 |
| 8,304 | SPARSI: Partitioning Sensitive Data amongst Multiple Adversaries | 2013 | VLDB | 4.5435639e-05 |
| 9,924 | On Saving Outliers for Better Clustering over Noisy Data | 2021 | SIGMOD | 4.2544238e-05 |
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