Yuri Rabinovich

The geometry of graphs and some of its algorithmic applications

We explore some implications of viewing graphs as geometric objects. This approach offers a new perspective on a number of graph-theoretic and algorithmic problems. There are several ways to model graphs geometrically and our main concern here is with geometric representations that respect the metric of the (possibly weighted) graph. Given a graph G we map its vertices to a normed space in an attempt to (i) Keep down the dimension of the host space and (ii) Guarantee a small distortion, i.e., make sure that distances between vertices in G closely match the distances between their geometric images. We develop efficient algorithms for embedding graphs low-dimensionally with a small distortion.<<ETX>>

Lower Bounds on the Distortion of Embedding Finite Metric Spaces in Graphs

Abstract. The main question discussed in this paper is how well a finite metric space of size n can be embedded into a graph with certain topological restrictions. The existing constructions of graph spanners imply that any n -point metric space can be represented by a (weighted) graph with n vertices and n1 +O(1/r) edges, with distances distorted by at most r . We show that this tradeoff between the number of edges and the distortion cannot be improved, and that it holds in a much more general setting. The main technical lemma claims that the metric space induced by an unweighted graph H of girth g cannot be embedded in a graph G (even if it is weighted) of smaller Euler characteristic, with distortion less than g/4 - 3/2 . In the special case when |V(G)| =|V(H)| and G has strictly less edges than H , an improved bound of g/3 - 1 is shown. In addition, we discuss the case χ(G) < χ(H) - 1 , as well as some interesting higher-dimensional analogues. The proofs employ basic techniques of algebraic topology.

Quadratic dynamical systems

The paper promotes the study of computational aspects, primarily the convergence rate, of nonlinear dynamical systems from a combinatorial perspective. The authors identify the class of symmetric quadratic systems. Such systems have been widely used to model phenomena in the natural sciences, and also provide an appropriate framework for the study of genetic algorithms in combinatorial optimisation. They prove several fundamental general properties of these systems, notably that every trajectory converges to a fixed point. They go on to give a detailed analysis of a quadratic system defined in a natural way on probability distributions over the set of matchings in a graph. In particular, they prove that convergence to the limit requires only polynomial time when the graph is a tree. This result demonstrates that such systems, though nonlinear, are amenable to quantitative analysis.<<ETX>>

Sphere packing and local majorities in graphs

The paper concerns some extremal problems on packing spheres in graphs and covering graphs by spheres. Tight bounds are provided for these problems on general graphs. The bounds are then applied to answer the following question: Let f be a nonnegative function defined on the vertices of a graph G, and suppose one has a lower bound on the local averages of f, i.e., on fs average over every j-neighborhood in G for j=1,. . .,r. What can be concluded globally? I.e, what can be said about the average of f over all G? This question arose in connection with issues of locality in distributed network computation. The average estimation problem with unit radius balls is also studied for some special classes of graphs.<<ETX>>

On average distortion of embedding metrics into the line and into L 1

We introduce and study the notion of the average distortion of a nonexpanding embedding of one metric space into another. Less sensitive than the multiplicative metric distortion, the average distortion captures well the global picture, and, overall, is a quite interesting new measure of metric proximity, related to the concentration of measure phenomenon. We establish close mutual relations between the MinCut- MaxFlow gap in a uniform-demand multicommodity flow, and the average distortion of embedding the suitable (dual) metric into l1. These relations are exploited to show that the shortest-path metrics of special (e.g., planar, bounded treewidth, etc.) graphs embed into l1 with constant average distortion. The main result of the paper claims that this remains true even if l1 is replaced with the line. This result is further sharpened for graphs of a bounded treewidth.

A computational view of population genetics

A Computational View of Population Genetics (preliminary version) Yuval Rabanit Yuri Rabinovicht Alistair Sinclair] This paper contributes to the study of nonlinear dynamical systems from a computational perspective. These systems are inherently more powerful than their linear counterparts (such as Markov chains), which have had a wide impact in Computer Science, and they seem likely to play an increasing role in future. However, there are as yet no general techniques available for handling the computational aspects of discrete nonlinear systems, and even the simplest examples seem very hard to analyze. We focus in this paper on a class of quadratic systems that are widely used as a model in population genetics and also in genetic algorithms. These systems describe a process where random matings occur between parental chromosomes via a mechanism known as “crossover”: i.e., children inherit pieces of genetic material from different parents according to some random rule. Our results concern two fundamental quantitative properties of crossover systems: 1. We develop a general technique for computing the rate of convergence to equilibrium. We apply this technique to obtain tight bounds on the rate of convergence in several cases of biological and computational interest. In general, we prove that these systems are “rapidly mixing”, in the sense that the convergence time is very small in comparison with the size of the state space. 2. We show that, for crossover systems, the classical quadratic system is a good model for the behavior of finite populations of small size. This stands in sharp contrast to recent results of Arora et al and Pudlak, who show that such a correspondence is unlikely to hold for general quadratic systems. tD~p~~t~ent Of Computer Science, University of TorontO, Toronto, Ontario M5S 1A4, Canada. Email: {rabani ,yuri}Q cs. toronto. edu. t Computer Science Division, University of California, Berkeley CA 94720-1776, U.S.A. Email: sinclair@cs .berkeley. edu. Perrmssion to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyri ht notice and the % title of the publication and Its dat~ appear, an notice IS gwen that copyin is by permission of tne Association of Computing ? Machinery o copy otherwise, or to republish, requires a fee andlor specific permission. STOC” 95, Las Vegas, Nevada, USA @ 1995 ACM 0-89791 -718-9/95/0005 .

Embedding k -Outerplanar Graphs into l 1

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On Complexity of the Subpattern Problem

We show that the shortest-path metric of any k-outerplanar graph, for any fixed k, can be approximated by a probability distribution over tree metrics with constant distortion, and hence also embedded into l1 with constant distortion. These graphs play a central role in polynomial time approximation schemes for many NP-hard optimization problems on general planar graphs, and include the family of weighted k × n planar grids.This result implies a constant upper bound on the ratio between the sparsest cut and the maximum concurrent flow in multicommodity networks for k-outerplanar graphs, thus extending a classical theorem of Okamura and Seymour [26] for outerplanar graphs, and of Gupta et al. [17] for treewidth-2 graphs. In addition, we obtain improved approximation ratios for k-outerplanar graphs on various problems for which approximation algorithms are based on probabilistic tree embeddings. We also conjecture that our random tree embeddings for k-outerplanar graphs can serve as a building block for more powerful l1 embeddings in future.

Witness sets for families of binary vectors

We study various computational aspects of the problem of determining whether, given a (fixed) permutation

A lower bound on the distortion of embedding planar metrics into Euclidean space

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