In this paper, we show that any n point metric space can be embedded into a distribution
over dominating tree metrics such that the expected stretch of any edge is O (log n). This …

The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be
covered using 2k balls of radius r. This concept for abstract metrics has been proposed as a …

Metric Embedding plays an important role in a vast range of application areas such as
computer vision, computational biology, machine learning, networking, statistics, and …

We devise a new embedding technique, which we call measured descent, based on
decomposing a metric space locally, at varying speeds, according to the density of some …

Many classical problems in geometry and analysis involve the gluing together of local
information to produce a coherent global picture. Inevitably, the difficulty of such a procedure …

We consider approximation algorithms for the metric labeling problem. This problem was
introduced in a paper by Kleinberg and Tardos J. ACM, 49 (2002), pp. 616--630 and …

Linial, London and Rabinovich [16] and Aumann and Rabani [3] proved that the min-cut max-
flow ratio for general maximum concurrent flow problems (when there are k commodities) is …

$\def\vecc# 1 {\boldsymbol {# 1}} $ We design a polynomial time algorithm that for any
weighted undirected graph $ G=(V, E,\vecc w) $ and sufficiently large $\delta> 1$, partitions …

The connection between integrality gaps and computational hardness of discrete
optimization problems is an intriguing question. In recent years, this connection has …

Given a capacitated graph G=(V,E) and a set of terminals K⊆V, how should we produce a
graph H only on the terminals K so that every (multicommodity) flow between the terminals in …