Published in: LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)
Wai Ming Tai. Optimal Coreset for Gaussian Kernel Density Estimation. In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 63:1-63:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
@InProceedings{tai:LIPIcs.SoCG.2022.63, author = {Tai, Wai Ming}, title = {{Optimal Coreset for Gaussian Kernel Density Estimation}}, booktitle = {38th International Symposium on Computational Geometry (SoCG 2022)}, pages = {63:1--63:15}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-227-3}, ISSN = {1868-8969}, year = {2022}, volume = {224}, editor = {Goaoc, Xavier and Kerber, Michael}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.63}, URN = {urn:nbn:de:0030-drops-160719}, doi = {10.4230/LIPIcs.SoCG.2022.63}, annote = {Keywords: Discrepancy Theory, Kernel Density Estimation, Coreset} }
Published in: LIPIcs, Volume 204, 29th Annual European Symposium on Algorithms (ESA 2021)
Jasper C.H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, and Wai Ming Tai. Finding an Approximate Mode of a Kernel Density Estimate. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 61:1-61:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
@InProceedings{lee_et_al:LIPIcs.ESA.2021.61, author = {Lee, Jasper C.H. and Li, Jerry and Musco, Christopher and Phillips, Jeff M. and Tai, Wai Ming}, title = {{Finding an Approximate Mode of a Kernel Density Estimate}}, booktitle = {29th Annual European Symposium on Algorithms (ESA 2021)}, pages = {61:1--61:19}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-204-4}, ISSN = {1868-8969}, year = {2021}, volume = {204}, editor = {Mutzel, Petra and Pagh, Rasmus and Herman, Grzegorz}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2021.61}, URN = {urn:nbn:de:0030-drops-146428}, doi = {10.4230/LIPIcs.ESA.2021.61}, annote = {Keywords: Kernel density estimation, Dimensionality reduction, Coresets, Means-shift} }
Published in: LIPIcs, Volume 176, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)
Jeff M. Phillips and Wai Ming Tai. The GaussianSketch for Almost Relative Error Kernel Distance. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 176, pp. 12:1-12:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
@InProceedings{phillips_et_al:LIPIcs.APPROX/RANDOM.2020.12, author = {Phillips, Jeff M. and Tai, Wai Ming}, title = {{The GaussianSketch for Almost Relative Error Kernel Distance}}, booktitle = {Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)}, pages = {12:1--12:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-164-1}, ISSN = {1868-8969}, year = {2020}, volume = {176}, editor = {Byrka, Jaros{\l}aw and Meka, Raghu}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2020.12}, URN = {urn:nbn:de:0030-drops-126150}, doi = {10.4230/LIPIcs.APPROX/RANDOM.2020.12}, annote = {Keywords: Kernel Distance, Kernel Density Estimation, Sketching} }
Published in: LIPIcs, Volume 99, 34th International Symposium on Computational Geometry (SoCG 2018)
Jeff M. Phillips and Wai Ming Tai. Near-Optimal Coresets of Kernel Density Estimates. In 34th International Symposium on Computational Geometry (SoCG 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 99, pp. 66:1-66:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
@InProceedings{phillips_et_al:LIPIcs.SoCG.2018.66, author = {Phillips, Jeff M. and Tai, Wai Ming}, title = {{Near-Optimal Coresets of Kernel Density Estimates}}, booktitle = {34th International Symposium on Computational Geometry (SoCG 2018)}, pages = {66:1--66:13}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-066-8}, ISSN = {1868-8969}, year = {2018}, volume = {99}, editor = {Speckmann, Bettina and T\'{o}th, Csaba D.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2018.66}, URN = {urn:nbn:de:0030-drops-87797}, doi = {10.4230/LIPIcs.SoCG.2018.66}, annote = {Keywords: Coresets, Kernel Density Estimate, Discrepancy} }
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