124 research outputs found
Multi-Embedding of Metric Spaces
Metric embedding has become a common technique in the design of algorithms.
Its applicability is often dependent on how high the embedding's distortion is.
For example, embedding finite metric space into trees may require linear
distortion as a function of its size. Using probabilistic metric embeddings,
the bound on the distortion reduces to logarithmic in the size.
We make a step in the direction of bypassing the lower bound on the
distortion in terms of the size of the metric. We define "multi-embeddings" of
metric spaces in which a point is mapped onto a set of points, while keeping
the target metric of polynomial size and preserving the distortion of paths.
The distortion obtained with such multi-embeddings into ultrametrics is at most
O(log Delta loglog Delta) where Delta is the aspect ratio of the metric. In
particular, for expander graphs, we are able to obtain constant distortion
embeddings into trees in contrast with the Omega(log n) lower bound for all
previous notions of embeddings.
We demonstrate the algorithmic application of the new embeddings for two
optimization problems: group Steiner tree and metrical task systems
Universal immersion spaces for edge-colored graphs and nearest-neighbor metrics
There exist finite universal immersion spaces for the following: (a) Edge-colored graphs of bounded degree and boundedly many colors. (b) Nearest-neighbor metrics of bounded degree and boundedly many edge lengths
Embedding Metrics into Ultrametrics and Graphs into Spanning Trees with Constant Average Distortion
This paper addresses the basic question of how well can a tree approximate
distances of a metric space or a graph. Given a graph, the problem of
constructing a spanning tree in a graph which strongly preserves distances in
the graph is a fundamental problem in network design. We present scaling
distortion embeddings where the distortion scales as a function of ,
with the guarantee that for each the distortion of a fraction
of all pairs is bounded accordingly. Such a bound implies, in
particular, that the \emph{average distortion} and -distortions are
small. Specifically, our embeddings have \emph{constant} average distortion and
-distortion. This follows from the following
results: we prove that any metric space embeds into an ultrametric with scaling
distortion . For the graph setting we prove that any
weighted graph contains a spanning tree with scaling distortion
. These bounds are tight even for embedding in arbitrary
trees.
For probabilistic embedding into spanning trees we prove a scaling distortion
of , which implies \emph{constant}
-distortion for every fixed .Comment: Extended abstrat apears in SODA 200
On Metric Ramsey-type Dichotomies
The classical Ramsey theorem, states that every graph contains either a large
clique or a large independent set. Here we investigate similar dichotomic
phenomena in the context of finite metric spaces. Namely, we prove statements
of the form "Every finite metric space contains a large subspace that is nearly
quilateral or far from being equilateral". We consider two distinct
interpretations for being "far from equilateral". Proximity among metric spaces
is quantified through the metric distortion D. We provide tight asymptotic
answers for these problems. In particular, we show that a phase transition
occurs at D=2.Comment: 14 pages, 0 figure
On some low distortion metric Ramsey problems
In this note, we consider the metric Ramsey problem for the normed spaces
l_p. Namely, given some 1=1, and an integer n, we ask
for the largest m such that every n-point metric space contains an m-point
subspace which embeds into l_p with distortion at most alpha. In
[arXiv:math.MG/0406353] it is shown that in the case of l_2, the dependence of
on alpha undergoes a phase transition at alpha=2. Here we consider this
problem for other l_p, and specifically the occurrence of a phase transition
for p other than 2. It is shown that a phase transition does occur at alpha=2
for every p in the interval [1,2]. For p>2 we are unable to determine the
answer, but estimates are provided for the possible location of such a phase
transition. We also study the analogous problem for isometric embedding and
show that for every 1<p<infinity there are arbitrarily large metric spaces, no
four points of which embed isometrically in l_p.Comment: 14 pages, to be published in Discrete and Computational Geometr
On metric Ramsey-type phenomena
The main question studied in this article may be viewed as a nonlinear
analogue of Dvoretzky's theorem in Banach space theory or as part of Ramsey
theory in combinatorics. Given a finite metric space on n points, we seek its
subspace of largest cardinality which can be embedded with a given distortion
in Hilbert space. We provide nearly tight upper and lower bounds on the
cardinality of this subspace in terms of n and the desired distortion. Our main
theorem states that for any epsilon>0, every n point metric space contains a
subset of size at least n^{1-\epsilon} which is embeddable in Hilbert space
with O(\frac{\log(1/\epsilon)}{\epsilon}) distortion. The bound on the
distortion is tight up to the log(1/\epsilon) factor. We further include a
comprehensive study of various other aspects of this problem.Comment: 67 pages, published versio
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