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Guy Even

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

15 papers
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Possible papers

15

STOC Conference 2022 Conference Paper

An extendable data structure for incremental stable perfect hashing

  • Ioana Oriana Bercea
  • Guy Even

We consider the problem of dynamically assigning n elements unique indices, known as hashcodes , in the range [(1+ o (1)) n ]. This problem is known as perfect hashing and is considered a fundamental building block in the design of more involved data structures. The challenge we address is that of designing a data structure that meets several, seemingly opposing, requirements: (1) the range and the space of the data structure must be, at all times, proportional to the current cardinality n t of the input set, and (2) the hashcodes it assigns must be stable in that the hashcode of an element must not change while the element is continuously in the set. A simple argument shows that these two desiderata are impossible to achieve when arbitrary deletions and insertions are allowed. In this paper, we show that one can achieve them when only insertions occur and, more generally, when the hashcode range and the space are allowed to grow as a function of the maximum cardinality N t of the set until time t . The data structure executes all operations in worst case constant time with high probability and requires space that is within a constant factor of the lower bound. In particular, this leads to a hash table design that does not need to move elements as its size grows. More generally, we present, as an application, a cyclic sequence of reductions between data structures that lead to the following bootstrapping result. Let B ( u , n ) denote the lower bound on the space of a dictionary for n elements over a universe [ u ]. Given a compact dynamic dictionary (i.e., space O ( B ( u , n ))), we can use it to build a dynamic dictionary with space B ( u , n )+ O ( n loglog n ). This reduction increases the time per operation by an additive constant and applies both to the extendable and non-extendable settings (failure probability is 1/ poly ( n ) per insertion).

FOCS Conference 2002 Conference Paper

Conflict-Free Colorings of Simple Geometric Regions with Applications to Frequency Assignment in Cellular Networks

  • Guy Even
  • Zvi Lotker
  • Dana Ron
  • Shakhar Smorodinsky

Motivated by a frequency assignment problem in cellular networks, we introduce and study a new coloring problem called minimum conflict-free coloring (min-CF-coloring). In its general form, the input of the min-CF-coloring problem is a set system (X, S), where each S /spl isin/ S is a subset of X. The output is a coloring X of the sets in S that satisfies the following constraint: for every x /spl isin/ X there exists a color i and a unique set S /spl isin/ S, such that x /spl isin/ S and /spl chi/(S) = i. The goal is to minimize the number of colors used by the coloring X. Min-CF-coloring of general set systems is not easier than the classic graph coloring problem. However, in view of our motivation, we consider set systems induced by simple geometric regions in the plane. In particular, we study disks (both congruent and non-congruent), axis-parallel rectangles (with a constant ratio between the smallest and largest rectangle) regular hexagons (with a constant ratio between the smallest and largest hexagon), and general congruent centrally-symmetric convex regions in the plane. In all cases we have coloring algorithms that use O(log n) colors (where n is the number of regions). For rectangles and hexagons we obtain a constant-ratio approximation algorithm when the ratio between the largest and smallest rectangle (hexagon) is a constant. We also show that, even in the case of unit disks, /spl Theta/(log n) colors may be necessary.

FOCS Conference 1996 Conference Paper

An 8-Approximation Algorithm for the Subset Feedback Vertex Set Problem

  • Guy Even
  • Joseph Naor
  • Leonid Zosin

We present an 8-approximation algorithm for the problem of finding a minimum weight subset feedback vertex set. The input in this problem consists of an undirected graph G=(V, E) with vertex weights w(v) and a subset of vertices S called special vertices. A cycle is called interesting if it contains at least one special vertex. A subset of vertices is called a subset feedback vertex set with respect to S if it intersects every interesting cycle The goal is to find a minimum weight subset feedback vertex set. The best pervious algorithm for the general case provided only a logarithmic approximation factor. The minimum weight subset feedback vertex set problem generalizes two NP-Complete problems: the minimum weight feedback vertex set problem in undirected graphs and the minimum weight multiway vertex cut problem. The main tool that we use in our algorithm and its analysis is a new version of multi-commodity flow which we call relaxed multi-commodity flow. Relaxed multi-commodity flow is a hybrid of multi-commodity flow and multi-terminal flow.

FOCS Conference 1995 Conference Paper

Divide-and-Conquer Approximation Algorithms via Spreading Metrics (Extended Abstract)

  • Guy Even
  • Joseph Naor
  • Satish Rao
  • Baruch Schieber

We present a novel divide-and-conquer paradigm for approximating NP-hard graph optimization problems. The paradigm models graph optimization problems that satisfy two properties: First, a divide-and-conquer approach is applicable. Second, a fractional spreading metric is computable in polynomial time. The spreading metric assigns fractional lengths to either edges or vertices of the input graph, such that all subgraphs on which the optimisation problem is non-trivial have large diameters. In addition, the spreading metric provides a lower bound, /spl tau/, on the cost of solving the optimization problem. We present a polynomial time approximation algorithm for problems modelled by our paradigm whose approximation factor is O (mi.