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pro vyhledávání: '"Burkhardt, Jakob"'
Autor:
Burkhardt, Jakob, Caragiannis, Ioannis, Fehrs, Karl, Russo, Matteo, Schwiegelshohn, Chris, Shyam, Sudarshan
Motivated by recent work in computational social choice, we extend the metric distortion framework to clustering problems. Given a set of $n$ agents located in an underlying metric space, our goal is to partition them into $k$ clusters, optimizing so
Externí odkaz:
http://arxiv.org/abs/2402.04035
Autor:
Schuetze, Konrad, Burkhardt, Jakob, Pankratz, Carlos, Eickhoff, Alexander, Boehringer, Alexander, Degenhart, Christina, Gebhard, Florian, Cintean, Raffael
Publikováno v:
Archives of Orthopaedic & Trauma Surgery; Jun2023, Vol. 143 Issue 6, p3155-3161, 7p
Akademický článek
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Publikováno v:
Hogräfer, M, Burkhardt, J & Schulz, H-J 2022, A Pipeline for Tailored Sampling for Progressive Visual Analytics . in J Bernard & M Angelini (eds), Proceedings of the 13th International EuroVis Workshop on Visual Analytics (EuroVA) . Eurographics Association, pp. 49-53, International EuroVis Workshop on Visual Analytics, Rome, Italy, 13/06/2022 . https://doi.org/10.2312/eurova.20221079
Progressive Visual Analytics enables analysts to interactively work with partial results from long-running computations early on instead of forcing them to wait. For very large datasets, the first step is to divide that input data into smaller chunks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pure_au_____::f78df2546cdebc723cf497c2cb48ed14
https://pure.au.dk/portal/da/publications/a-pipeline-for-tailored-sampling-for-progressive-visual-analytics(eda327b9-3ea2-4578-9080-594ddb27ad26).html
https://pure.au.dk/portal/da/publications/a-pipeline-for-tailored-sampling-for-progressive-visual-analytics(eda327b9-3ea2-4578-9080-594ddb27ad26).html