Methods › General › Clustering › Coresets › Papers where code ran, page 1
Coresets
Papers archive 2025-07-28
archive papers tagged: 103 · with a code link: 41 · where Syntology ran a sample: 15 (14 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (15 of 103 tagged: 14 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument)
Syntology We ran code from the paper's repository; we did not isolate this method inside it.
Page 1 of 1: papers 1 to 15 of the 15 tagged papers where Syntology ran at least one harvested sample (14 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.
Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.
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Small coresets via negative dependence: DPPs, linear statistics, and concentration 1 Nov 2024 · 1 repository · arXiv:2411.00611Syntology official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples)
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Data subsampling for Poisson regression with pth-root-link 30 Oct 2024 · 1 repository · arXiv:2410.22872Syntology official (archive's flag): 9 ran · 9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 10 harvested samples) · 10 pointer-only (licence)
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Supervised Kernel Thinning 17 Oct 2024 · 1 repository · arXiv:2410.13749Syntology official (archive's flag): 10 ran · 10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified (of 14 harvested samples)
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Turnstile ℓₚ leverage score sampling with applications 1 Jun 2024 · 1 repository · arXiv:2406.00339Syntology official (archive's flag): 8 ran · 8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 8 harvested samples) · 8 pointer-only (licence)
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Scalable Learning of Item Response Theory Models 1 Mar 2024 · 1 repository · arXiv:2403.00680Syntology official (archive's flag): 13 ran · 13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 13 harvested samples) · 13 pointer-only (licence)
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Towards Sustainable Learning: Coresets for Data-efficient Deep Learning 2 Jun 2023 · 1 repository · arXiv:2306.01244Syntology official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample)
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Regularizing Second-Order Influences for Continual Learning 20 Apr 2023 · 1 repository · arXiv:2304.10177Syntology official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples)
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Efficient Dataset Distillation Using Random Feature Approximation 21 Oct 2022 · 2 repositories · arXiv:2210.12067Syntology official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified (of 2 harvested samples) · 2 pointer-only (licence)
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Adversarial Coreset Selection for Efficient Robust Training 13 Sep 2022 · 1 repository · arXiv:2209.05785Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples) · 3 pointer-only (licence)
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An Empirical Evaluation of k-Means Coresets 3 Jul 2022 · 1 repository · arXiv:2207.00966Syntology official (archive's flag): 6 ran · 6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 6 harvested samples) · 6 pointer-only (licence)
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Towards Total Recall in Industrial Anomaly Detection 15 Jun 2021 · 18 repositories · arXiv:2106.08265Syntology official (archive's flag): 4 ran · 28 ran (of which 0 constructed an object rather than computing a result; 26 with no instrument failure: 1 honoured, 1 violated, 24 with no contract checked; 2 where Syntology's instrument failed) · 8 unverified (of 36 harvested samples) · 4 pointer-only (licence)
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Coresets for Regressions with Panel Data 2 Nov 2020 · 1 repository · arXiv:2011.00981Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective 1 Jul 2020 · 1 repository · arXiv:2007.00715Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
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Coresets via Bilevel Optimization for Continual Learning and Streaming 6 Jun 2020 · 1 repository · arXiv:2006.03875Syntology official (archive's flag): 1 ran · 1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result (of 1 harvested sample)
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Active Learning for Convolutional Neural Networks: A Core-Set Approach 1 Aug 2017 · 11 repositories · arXiv:1708.00489Syntology community repositories only · 2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 4 harvested samples) · 4 pointer-only (licence)