Results 1  10
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29
Iterated Nearest Neighbors and Finding Minimal Polytopes
, 1994
"... Weintroduce a new method for finding several types of optimal kpoint sets, minimizing perimeter, diameter, circumradius, and related measures, by testing sets of the O(k) nearest neighbors to each point. We argue that this is better in a number of ways than previous algorithms, whichwere based o ..."
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Cited by 56 (6 self)
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Weintroduce a new method for finding several types of optimal kpoint sets, minimizing perimeter, diameter, circumradius, and related measures, by testing sets of the O(k) nearest neighbors to each point. We argue that this is better in a number of ways than previous algorithms, whichwere based on high order Voronoi diagrams. Our technique allows us for the first time to efficiently maintain minimal sets as new points are inserted, to generalize our algorithms to higher dimensions, to find minimal convex kvertex polygons and polytopes, and to improvemany previous results. Weachievemany of our results via a new algorithm for finding rectilinear nearest neighbors in the plane in time O(n log n+kn). We also demonstrate a related technique for finding minimum area kpoint sets in the plane, based on testing sets of nearest vertical neighbors to each line segment determined by a pair of points. A generalization of this technique also allows us to find minimum volume and boundary measure sets in arbitrary dimensions.
Geometric Applications of a Randomized Optimization Technique
 Discrete Comput. Geom
, 1999
"... We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase the expected time complexity by only a constant factor and eliminate extra logarithmic factors in previous, often more complicated, ..."
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Cited by 53 (6 self)
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We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase the expected time complexity by only a constant factor and eliminate extra logarithmic factors in previous, often more complicated, deterministic approaches (such as parametric searching). Faster algorithms are thus obtained for a variety of problems in computational geometry: finding minimal kpoint subsets, matching point sets under translation, computing rectilinear pcenters and discrete 1centers, and solving linear programs with k violations. 1 Introduction Consider the classic randomized algorithm for finding the minimum of r numbers minfA[1]; : : : ; A[r]g: Algorithm randmin 1. randomly pick a permutation hi 1 ; : : : ; i r i of h1; : : : ; ri 2. t /1 3. for k = 1; : : : ; r do 4. if A[i k ] ! t then 5. t / A[i k ] 6. return t By a wellknown fact [27, 44], the expected number of times that step 5 is execut...
Faster Construction of Planar Twocenters
, 1997
"... Improving on a recent breakthrough of Sharir, we find two minimumradius circular disks covering a planar point set, in randomized expected time O(n log 2 n). 1 Introduction The kcenter problem for a point set S is to find k points (called centers, usually not required to be a subset of S) such ..."
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Cited by 47 (0 self)
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Improving on a recent breakthrough of Sharir, we find two minimumradius circular disks covering a planar point set, in randomized expected time O(n log 2 n). 1 Introduction The kcenter problem for a point set S is to find k points (called centers, usually not required to be a subset of S) such that the maximum distance from any point in S to the nearest center is minimized. A case of particular interest is the planar twocenter problem [4], which can be viewed less abstractly as one of covering a set of points in the plane by two congruent circular disks, in such a way as to minimize the radius r # of the disks. For a long time the best algorithms for this problem had time bounds of the form O(n 2 log c n) [1, 5, 12, 11]. In a recent breakthrough, Sharir [16] greatly improved all of these algorithms, giving a twocenter algorithm with running time O(n log c n). The basic idea is to search for different types of partition depending on the relative positions of the two disk...
Optimal Partition of QoS Requirements on Unicast Paths and Multicast Trees
 IEEE/ACM Transactions on Networking
, 1998
"... We investigate the problem of optimal resource allocation for endtoend QoS requirements on unicast paths and multicast trees. Specifically, we consider a framework in which resource allocation is based on local QoS requirements at each network link, and associated with each link is a cost function ..."
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Cited by 45 (6 self)
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We investigate the problem of optimal resource allocation for endtoend QoS requirements on unicast paths and multicast trees. Specifically, we consider a framework in which resource allocation is based on local QoS requirements at each network link, and associated with each link is a cost function that increases with the severity of the QoS requirement. Accordingly, the problem that we address is how to partition an endtoend QoS requirement into local requirements, such that the overall cost is minimized. We establish efficient (polynomial) solutions for both unicast and multicast connections. These results provide the required foundations for the corresponding QoS routing schemes, which identify either paths or trees that lead to minimal overall cost. In addition, we show that our framework provides better tools for coping with other fundamental multicast problems, such as dynamic tree maintenance. Keywords  QoS, QoSdependent costs, Multicast, Routing, Broadband ne...
Rectilinear and Polygonal pPiercing and pCenter Problems
 In Proc. 12th Annu. ACM Sympos. Comput. Geom
, 1996
"... We consider the ppiercing problem, in which we are given a collection of regions, and wish to determine whether there exists a set of p points that intersects each of the given regions. We give linear or nearlinear algorithms for small values of p in cases where the given regions are either axispa ..."
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Cited by 30 (1 self)
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We consider the ppiercing problem, in which we are given a collection of regions, and wish to determine whether there exists a set of p points that intersects each of the given regions. We give linear or nearlinear algorithms for small values of p in cases where the given regions are either axisparallel rectangles or convex coriented polygons in the plane (i.e., convex polygons with sides from a fixed finite set of directions) . We also investigate the planar rectilinear (and polygonal) pcenter problem, in which we are given a set S of n points in the plane, and wish to find p axisparallel congruent squares (isothetic copies of some given convex polygon, respectively) of smallest possible size whose union covers S. We also study several generalizations of these problems. New results are a lineartime solution for the rectilinear 3center problem (by showing that this problem can be formulated as an LPtype problem and by exhibiting a relation to Helly numbers). We give O(n log n...
Path Problems in Graphs
 COMPUTING SUPPL
, 1989
"... A large variety of problems in computer science can be viewed from a common viewpoint as instances of "algebraic" path problems. Among them are of course path problems in graphs such as the shortest path problem or problems of finding optimal paths with respect to more generally defined objective ..."
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Cited by 27 (0 self)
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A large variety of problems in computer science can be viewed from a common viewpoint as instances of "algebraic" path problems. Among them are of course path problems in graphs such as the shortest path problem or problems of finding optimal paths with respect to more generally defined objective functions; but also graph problems whose formulations do not directly involve the concept of a path, such as finding all bridges and articulation points of a graph; Moreover, there are even problems which seemingly have nothing to do with graphs, such as the solution of systems of linear equations, partial differentiation, or the determination of the regular expression describing the language accepted by a finite automaton. We describe the relation among these problems and their common algebraic foundation. We survey algorithms for solving them: vertex elimination algorithms such as GaußJordan elimination; and iterative algorithms such as the "classical" Jacobi and GaußSeidel iteration.
Monitoring the dynamic web to respond to continuous queries
 In Proceedings of the Twelfth International World Wide Web Conference
, 2003
"... Our Continuous Adaptive Monitoring (CAM) system provides responses for continuous queries by monitoring and extracting information scattered across the web. Continuous queries are the queries for which responses given to users must be continuously updated, as the sources of interest get updated. Suc ..."
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Cited by 23 (1 self)
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Our Continuous Adaptive Monitoring (CAM) system provides responses for continuous queries by monitoring and extracting information scattered across the web. Continuous queries are the queries for which responses given to users must be continuously updated, as the sources of interest get updated. Such queries occur, for instance, during online decision making, e.g., traffic flow control, weather monitoring etc. Whereas pushbased techniques may be able to refresh query results meeting user requirements, they do not scale well. With the pull based approach, the problem of keeping the responses current reduces to the problem of deciding how often to visit a source to determine if and how it has been modified so that a user response can be updated accordingly. As should be evident, periodical monitoring is not scalable. Also, it can lead to huge wastage of monitoring resources. Hence CAM employs a multiphase approach. In the tracking phase, changes to an initially identified set of relevant pages, are tracked. From the observed change characteristics of these pages, a probabilistic model of their change behaviour is formulated and weights are assigned to pages to denote their importance for the current queries. Based on these statistics, during the next phase, the Resource Allocation phase, resources, needed to continuously monitor these pages for changes, are allocated. Given these resource allocations, the Scheduling phase produces an optimal achievable schedule of monitoring. An experimental evaluation of our approach compared to prior approaches on synthetic data for crawling dynamic web pages shows the effectiveness of our approach to monitoring dynamic changes. For example, by monitoring just 5 % of the possible change instances, CAM is able to return 90 % of the changed information to the users. In this demonstration, we show how CAM keeps users uptodate with respect to a set of ongoing sports related events. 1.
Probabilistic Arithmetic
, 1989
"... This thesis develops the idea of probabilistic arithmetic. The aim is to replace arithmetic operations on numbers with arithmetic operations on random variables. Specifically, we are interested in numerical methods of calculating convolutions of probability distributions. The longterm goal is to ..."
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Cited by 13 (0 self)
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This thesis develops the idea of probabilistic arithmetic. The aim is to replace arithmetic operations on numbers with arithmetic operations on random variables. Specifically, we are interested in numerical methods of calculating convolutions of probability distributions. The longterm goal is to be able to handle random problems (such as the determination of the distribution of the roots of random algebraic equations) using algorithms which have been developed for the deterministic case. To this end, in this thesis we survey a number of previously proposed methods for calculating convolutions and representing probability distributions and examine their defects. We develop some new results for some of these methods (the Laguerre transform and the histogram method), but ultimately find them unsuitable. We find that the details on how the ordinary convolution equations are calculated are
A nonlinear Knapsack Problem
 Operations Research Letters
, 1995
"... The nonlinear Knapsack problem is to maximize a separable concave objective function, subject to a single "packing" constraint, in nonnegative variables. We consider this problem in integer and continuous variables, and also when the packing constraint is convex. Although the nonlinear Knapsack prob ..."
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Cited by 10 (0 self)
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The nonlinear Knapsack problem is to maximize a separable concave objective function, subject to a single "packing" constraint, in nonnegative variables. We consider this problem in integer and continuous variables, and also when the packing constraint is convex. Although the nonlinear Knapsack problem appears difficult in comparison with the linear Knapsack problem, we prove that its complexity is similar. We demonstrate for the nonlinear Knapsack problem in n integer variables and knapsack volume limit B, a fully polynomial approximation scheme with running time ()((1/e 2) (n + l/e2)) (omitting polylog terms); and for the continuous case an algorithm delivering an eaccurate solution in O(nlog(B/~)) operations.
On Enumerating and Selecting Distances
 Int. J. Comput. Geom. Appl
, 1999
"... Given an npoint set, the problems of enumerating the k closest pairs and selecting the kth smallest distance are revisited. For the enumeration problem, we give simpler randomized and deterministic algorithms with O(n log n + k) running time in any fixeddimensional Euclidean space. For the selec ..."
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Cited by 9 (2 self)
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Given an npoint set, the problems of enumerating the k closest pairs and selecting the kth smallest distance are revisited. For the enumeration problem, we give simpler randomized and deterministic algorithms with O(n log n + k) running time in any fixeddimensional Euclidean space. For the selection problem, we give a randomized algorithm with running time O(n log n + n 2=3 k 1=3 log 5=3 n). We also describe outputsensitive results for halfspace range counting that are of use in more general distance selection problems. None of our algorithms requires parametric search. Keywords: distance enumeration, distance selection, closest pairs, range counting, randomized algorithms. 1 Introduction Finding the closest pair of an npoint set has a long history in computational geometry (see [34] for a nice survey). In the plane, the problem can be solved in O(n log n) time using the Delaunay triangulation. In an arbitrary fixed dimension d, the first O(n log n) algorithm, based on di...