Multi-embedding and path approximation of metric spaces

Yair Bartal, Manor Mendel · 2003

Metric embeddings have become a frequent tool in the design of algorithms. The applicability is often dependent on how high the embedding's distortion is. For example embedding into ultrametrics (or arbitrary trees) requires linear distortion. Using probabilistic metric embeddings, the bound reduces to O(log n log log n). Yet, the lower bound is still logarithmic. We make

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