Computing k-Regret Minimizing Sets
Summary: Proposes k-regret minimizing sets as a relaxed data-summary: small R approximates D's top-k results via top-1 queries. In 2D, optimal R via DP plane-sweep; in higher dimensions, a greedy LP-based algorithm yields compact summaries despite NP-hardness. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sean Chester
- 2. Alex Thomo
- 3. S. Venkatesh
- 4. Sue Whitesides
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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 |
|---|---|---|---|---|
| 428 | The Onion Technique: Indexing for Linear Optimization Queries | 2000 | SIGMOD | 0.0002349868 |
| 913 | Finding k-Dominant Skylines in High Dimensional Space | 2006 | SIGMOD | 0.00015372758 |
| 1,070 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014274615 |
| 2,621 | Interactive Regret Minimization | 2012 | SIGMOD | 8.4408945e-05 |
| 3,665 | Ad-hoc Top-k Query Answering for Data Streams | 2007 | VLDB | 6.8631567e-05 |
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| 5,906 | k-Regret Queries with Nonlinear Utilities | 2015 | VLDB | 5.274596e-05 |
| 6,804 | RRR: Rank-Regret Representative | 2019 | SIGMOD | 4.917138e-05 |
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| 9,753 | Minimum Coresets for Maxima Representation of Multidimensional Data | 2021 | PODS | 4.2856385e-05 |
| 1,070 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014274615 |
| 5,259 | Efficient k-Regret Query Algorithm with Restriction-free Bound for any Dimensionality | 2018 | SIGMOD | 5.5972902e-05 |
| 6,816 | A Unified Optimization Algorithm For Solving "Regret-Minimizing Representative" Problems | 2020 | VLDB | 4.9115662e-05 |
| 5,113 | Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative | 2017 | SIGMOD | 5.6827696e-05 |