DBLP - Melanie Schmidt
Google Scholar - Melanie Schmidt

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2021

Anonymization via Clustering of Locations in Road Networks, JH Haunert, D Schmidt, M Schmidt, GIScience 2021 Short Paper Proceedings

Coresets for constrained k-median and k-means clustering in low dimensional Euclidean space, M Schmidt, J Wargalla, arXiv preprint arXiv:2106.07319

Mapping Brain Clustering to Reproduce Missing MRI Scancs, G Baldini, M Schmidt, C Zäske, L Caldeira, Universität zu Köln

Upper and Lower Bounds for Complete Linkage in General Metric Spaces, A Arutyunova, A Großwendt, H Röglin, M Schmidt, J Wargalla, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021)

2020

Achieving anonymity via weak lower bound constraints for k-median and k-means, A Arutyunova, M Schmidt, STACS 2021, arXiv preprint arXiv:2009.03078

Turning Big Data Into Tiny Data: Constant-Size Coresets for -Means, PCA, and Projective Clustering, D Feldman, M Schmidt, C Sohler, SIAM Journal on Computing 49 (3), 601-657

2019

Noisy, Greedy and Not So Greedy k-means++, A Bhattacharya, J Eube, H Röglin, M Schmidt, ESA 2020, arXiv preprint arXiv:1912.00653

Fair Coresets and Streaming Algorithms for Fair k-means, M Schmidt, C Schwiegelshohn, C Sohler, International Workshop on Approximation and Online Algorithms, 232-251

Fully dynamic hierarchical diameter k-clustering and k-center, M Schmidt, C Sohler, arXiv preprint arXiv:1908.02645

Sublinear data structures for short Fréchet queries, A Driemel, I Psarros, M Schmidt, arXiv preprint arXiv:1907.04420

Analysis of Ward's method, A Großwendt, H Röglin, M Schmidt, Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms

2018

On the cost of essentially fair clusterings, IO Bercea, M Groß, S Khuller, A Kumar, C Rösner, DR Schmidt, M. Schmidt, arXiv preprint arXiv:1811.10319

Privacy preserving clustering with constraints, C Rösner, M Schmidt, ICALP 2018, also: arXiv preprint arXiv:1802.02497

Randomized Algorithms and Probabilistic Analysis, H Röglin, M Schmidt,

A Local-Search Algorithm for Steiner Forest, J Matuschke, M Groß, A Gupta, A Kumar, DR Schmidt, M Schmidt, J Verschae, ITCS 2018, Leibniz International Proceedings in Informatics, 31: 1-31: 17

2017

Improved and simplified inapproximability for k-means, E Lee, M Schmidt, J Wright, Information Processing Letters 120, 40-43

2016

Approximation algorithms for aversion k-clustering via local k-median, A Gupta, G Guruganesh, M Schmidt, ICALP 2016

Theoretical Analysis of the k-Means Algorithm–A Survey, J Blömer, C Lammersen, M Schmidt, C Sohler, Algorithm Engineering, 81-116

2015

Solving k-means on High-dimensional Big Data, JPW Kappmeier, DR Schmidt, M Schmidt, Experimental Algorithms, also arXiv preprint arXiv:1502.04265, 2015/2/15

Kernmengen und Datenstromalgorithmen für das k-means Problem und verwandte Zielfunktionen im Clustering, M Schmidt, Ausgezeichnete Informatikdissertationen 2014

2014

Earliest arrival flows in networks with multiple sinks, M Schmidt, M Skutella, Discrete Applied Mathematics 164, 320-327

Coresets and streaming algorithms for the k-means problem and related clustering objectives, M Schmidt, TU Dortmund,

2013

PROBI: A Heuristic for the probabilistic k-median problem, H Fichtenberger, M Schmidt, arXiv preprint arXiv:1309.5781

BICO: BIRCH meets coresets for k-means clustering, H Fichtenberger, M Gillé, M Schmidt, C Schwiegelshohn, C Sohler, European Symposium on Algorithms, 481-492

Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering, D Feldman, M Schmidt, C Sohler, SODA 2013, 1434-1453

2012

Approximating Earliest Arrival Flows in Arbitrary Networks, M Groß, JP Kappmeier, D Schmidt, M Schmidt, ESA 2012, 551-562

2011

Probabilistic k-Median Clustering in Data Streams, C Lammersen, M Schmidt, C Sohler, WAOA 2012 / Technical Report 2011

2010

On the use of network flow techniques for assigning evacuees to exits, D Dressler, M Groß, JP Kappmeier, T Kelter, J Kulbatzki, D Plümpe, G Schlechter, M Schmidt, M Skutella, S Temme, Procedia Engineering 3, 205-215