On Random Perfect Matchings in Metric Spaces with Not-too-large Diameters

Author:

Chang Ching-Lueh

Funder

Ministry of Science and Technology, Taiwan

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Theoretical Computer Science

Reference19 articles.

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2. Bartal, Y., Mendel, M.: Multiembedding of metric spaces. SIAM J. Comput. 34(1), 248–259 (2004)

3. Chang, C.-L.: On Las Vegas approximations for metric 1-median selection. Inf. Process. Lett. 146, 44–48 (2019)

4. Chechik, S., Cohen, E., Kaplan, H.: Average distance queries through weighted samples in graphs and metric spaces: High scalability with tight statistical guarantees. Inproceedings of the 18th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems & the 19th International Workshop on Randomization and Computation, pp. 659–679 (2015)

5. Chen, Y., Kannan, S., Khanna, S.: Sublinear algorithms and lower bounds for metric TSP cost estimation. In: Inproceedings of the 47th International Colloquium on Automata, Languages, and Programming, pp. 31:1–30:19 (2020)

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