Ingo Wegener. - Thomas Jansen 001; Melanie Schmidt 001; Dirk Sudholt; Carsten Witt; Christine Zarges (Evol. Comput., 2009)

Kreuzzahlrätsel: Sudokus waren gestern. - Martin Groß 001; Daniel Plümpe; Melanie Schmidt 001 (Inform. Spektrum, 2009)

Testing Euclidean Spanners. - Frank Hellweg; Melanie Schmidt 001; Christian Sohler (ESA (1), 2010)

Testing Euclidean Spanners. - Frank Hellweg; Melanie Schmidt 001; Christian Sohler (Property Testing, 2010)

Approximating Earliest Arrival Flows in Arbitrary Networks. - Martin Groß 001; Jan-Philipp W. Kappmeier; Daniel R. Schmidt 001; Melanie Schmidt 001 (ESA, 2012)

BICO: BIRCH Meets Coresets for k-Means Clustering. - Hendrik Fichtenberger; Marc Gillé; Melanie Schmidt 001; Chris Schwiegelshohn; Christian Sohler (ESA, 2013)

Turning big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering. - Dan Feldman; Melanie Schmidt 001; Christian Sohler (SODA, 2013)

PROBI: A Heuristic for the probabilistic k-median problem. - Hendrik Fichtenberger; Melanie Schmidt 001 (CoRR, 2013)

Coresets and streaming algorithms for the k-means problem and related clustering objectives. - Melanie Schmidt 001 (2014)

Kernmengen und Datenstromalgorithmen für das k-means Problem und verwandte Zielfunktionen im Clustering. - Melanie Schmidt 001 (Ausgezeichnete Informatikdissertationen, 2014)

Earliest arrival flows in networks with multiple sinks. - Melanie Schmidt 001; Martin Skutella (Discret. Appl. Math., 2014)

Solving k-means on High-Dimensional Big Data. - Jan-Philipp W. Kappmeier; Daniel R. Schmidt 001; Melanie Schmidt 001 (SEA, 2015)

Probabilistic k-Median Clustering in Data Streams. - Christiane Lammersen; Melanie Schmidt 001; Christian Sohler (Theory Comput. Syst., 2015)

Approximation Algorithms for Aversion k-Clustering via Local k-Median. - Anupam Gupta 001; Guru Guruganesh; Melanie Schmidt 001 (ICALP, 2016)

Theoretical Analysis of the $k$-Means Algorithm - A Survey. - Johannes Blömer; Christiane Lammersen; Melanie Schmidt 001; Christian Sohler (CoRR, 2016)

Theoretical Analysis of the k-Means Algorithm - A Survey. - Johannes Blömer; Christiane Lammersen; Melanie Schmidt 001; Christian Sohler (Algorithm Engineering, 2016)

Improved and simplified inapproximability for k-means. - Euiwoong Lee; Melanie Schmidt 001; John Wright 004 (Inf. Process. Lett., 2017)

Privacy Preserving Clustering with Constraints. - Clemens Rösner; Melanie Schmidt 001 (ICALP, 2018)

A Local-Search Algorithm for Steiner Forest. - Martin Groß 001; Anupam Gupta 001; Amit Kumar 001; Jannik Matuschke; Daniel R. Schmidt 001; Melanie Schmidt 001; José Verschae (ITCS, 2018)

Fair Coresets and Streaming Algorithms for Fair k-Means Clustering. - Melanie Schmidt 001; Chris Schwiegelshohn; Christian Sohler (CoRR, 2018)

On the Cost of Essentially Fair Clusterings. - Ioana Oriana Bercea; Martin Groß 001; Samir Khuller; Aounon Kumar; Clemens Rösner; Daniel R. Schmidt 001; Melanie Schmidt 001 (APPROX-RANDOM, 2019)

Analysis of Ward's Method. - Anna Großwendt; Heiko Röglin; Melanie Schmidt 001 (SODA, 2019)

Fair Coresets and Streaming Algorithms for Fair k-means. - Melanie Schmidt 001; Chris Schwiegelshohn; Christian Sohler (WAOA, 2019)

Sublinear data structures for short Fréchet queries. - Anne Driemel; Ioannis Psarros; Melanie Schmidt 001 (CoRR, 2019)

Fully dynamic hierarchical diameter k-clustering and k-center. - Melanie Schmidt 001; Christian Sohler (CoRR, 2019)

Noisy, Greedy and Not so Greedy k-Means++. - Anup Bhattacharya; Jan Eube; Heiko Röglin; Melanie Schmidt 001 (ESA, 2020)

Turning Big Data Into Tiny Data: Constant-Size Coresets for k-Means, PCA, and Projective Clustering. - Dan Feldman; Melanie Schmidt 001; Christian Sohler (SIAM J. Comput., 2020)

Achieving Anonymity via Weak Lower Bound Constraints for k-Median and k-Means. - Anna Arutyunova; Melanie Schmidt 001 (STACS, 2021)

Coresets for constrained k-median and k-means clustering in low dimensional Euclidean space. - Melanie Schmidt 001; Julian Wargalla (CoRR, 2021)

Connected k-Center and k-Diameter Clustering. - Lukas Drexler; Jan Eube; Kelin Luo; Heiko Röglin; Melanie Schmidt 001; Julian Wargalla (ICALP, 2023)

Faster Query Times for Fully Dynamic k-Center Clustering with Outliers. - Leyla Biabani; Annika Hennes; Morteza Monemizadeh; Melanie Schmidt 001 (NeurIPS, 2023)

Approximating Fair k-Min-Sum-Radii in Euclidean Space. - Lukas Drexler; Annika Hennes; Abhiruk Lahiri; Melanie Schmidt 001; Julian Wargalla (WAOA, 2023)

Approximating Fair k-Min-Sum-Radii in Rd. - Lukas Drexler; Annika Hennes; Abhiruk Lahiri; Melanie Schmidt 001; Julian Wargalla (CoRR, 2023)

MRI Scan Synthesis Methods Based on Clustering and Pix2Pix. - Giulia Baldini 001; Melanie Schmidt 001; Charlotte Zäske; Liliana Lourenco Caldeira (AIME (2), 2024)

FPT Approximations for Fair k-Min-Sum-Radii. - Lena Carta; Lukas Drexler; Annika Hennes; Clemens Rösner; Melanie Schmidt 001 (ISAAC, 2024)

Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering. - Anna Arutyunova; Jan Eube; Heiko Röglin; Melanie Schmidt 001; Sarah Sturm; Julian Wargalla (NeurIPS, 2024)

Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces. - Leyla Biabani; Annika Hennes; Denise La Gordt Dillie; Morteza Monemizadeh; Melanie Schmidt 001 (NeurIPS, 2024)

Local Search k-means++ with Foresight. - Theo Conrads; Lukas Drexler; Joshua Könen; Daniel R. Schmidt 001; Melanie Schmidt 001 (SEA, 2024)

FPT Approximations for Fair k-Min-Sum-Radii. - Lena Carta; Lukas Drexler; Annika Hennes; Clemens Rösner; Melanie Schmidt 001 (CoRR, 2024)

Upper and lower bounds for complete linkage in general metric spaces. - Anna Arutyunova; Anna Großwendt; Heiko Röglin; Melanie Schmidt 001; Julian Wargalla (Mach. Learn., 2024)

algo-hhu/FLSpp. - Lukas Drexler; Joshua Könen; Daniel R. Schmidt 001; Melanie Schmidt 001; Giulia Baldini 001 (DROPS Artifacts, 2024)

Connected k-Center and k-Diameter Clustering. - Lukas Drexler; Jan Eube; Kelin Luo; Dorian Reineccius; Heiko Röglin; Melanie Schmidt 001; Julian Wargalla (Algorithmica, 2024)

Connected k-Median with Disjoint and Non-disjoint Clusters. - Jan Eube; Kelin Luo; Dorian Reineccius; Heiko Röglin; Melanie Schmidt 001 (CoRR, 2025)