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Sariel Har-Peled

Publications and source records attributed to Sariel Har-Peled.

At least 127 records · Page 7Linked to original sources
arXiv2013

Approximating Minimization Diagrams and Generalized Proximity Search

We investigate the classes of functions whose minimization diagrams can be approximated efficiently in \Re^d. We present a general framework and a data-structure that can be used to approximate the minimization diagram of such functions. The resulting data-structure has near linear size and can answer queries in logarithmic time. Applications include approximating the Voronoi diagram of (additively or multiplicatively) weighted points. Our technique also works for more general distance functions, such as metrics induced by convex bodies, and the nearest furthest-neighbor distance to a set of point sets. Interestingly, our framework works also for distance functions that do not comply with the triangle inequality. For many of these functions no near-linear size approximation was known before.

cs.CG↗
arXiv2013

Peeling the Grid

Consider the set of points formed by the integer $n \times n$ grid, and the process that in each iteration removes from the point set the vertices of its convex-hull. Here, we prove that the number of iterations of this process is O(n^{4/3}); that is, the number of convex layers of the $n\times n$ grid is Θ(n^{4/3}).

cs.DM↗
arXiv2012

Approximate Nearest Neighbor Search for Low Dimensional Queries

We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension, while the data is high-dimensional. We show that this problem can be solved efficiently despite the high dimensionality of the data.

cs.CG↗
arXiv2012

Fréchet Distance Revisited and Extended

Given two simplicial complexes in R^d, and start and end vertices in each complex, we show how to compute curves (in each complex) between these vertices, such that the Fréchet distance between these curves is minimized. As a polygonal curve is a complex, this generalizes the regular notion of weak Fréchet distance between curves. We also generalize the algorithm to handle an input of k simplicial complexes. Using this new algorithm we can solve a slew of new problems, from computing a mean curve for a given collection of curves, to various motion planning problems. Additionally, we show that for the mean curve problem, when the k input curves are c-packed, one can (1+epsilon)-approximate the mean curve in near linear time, for fixed k and epsilon. Additionally, we present an algorithm for computing the strong Fréchet distance between two curves, which is simpler than previous algorithms, and avoids using parametric search.

cs.CG↗
arXiv2012

Approximating the Fréchet Distance for Realistic Curves in Near Linear Time

We present simple and practical $(1+\eps)$-approximation algorithm for the Frechet distance between curves. To analyze this algorithm we introduce a new realistic family of curves, $c$-packed curves, that is closed under simplification. We believe the notion of $c$-packed curves to be of independent interest. We show that our algorithm has near linear running time for $c$-packed curves, and show similar results for other input models.

cs.CG↗
arXiv2012

Faster Approximate Distance Queries and Compact Routing in Sparse Graphs

A distance oracle is a compact representation of the shortest distance matrix of a graph. It can be queried to approximate shortest paths between any pair of vertices. Any distance oracle that returns paths of worst-case stretch (2k-1) must require space $Ω(n^{1 + 1/k})$ for graphs of n nodes. The hard cases that enforce this lower bound are, however, rather dense graphs with average degree Ω(n^{1/k}). We present distance oracles that, for sparse graphs, substantially break the lower bound barrier at the expense of higher query time. For any 1 \leq α\leq n, our distance oracles can return stretch 2 paths using O(m + n^2/α) space and stretch 3 paths using O(m + n^2/α^2) space, at the expense of O(αm/n) query time. By setting appropriate values of α, we get the first distance oracles that have size linear in the size of the graph, and return constant stretch paths in non-trivial query time. The query time can be further reduced to O(α), by using an additional O(m α) space for all our distance oracles, or at the cost of a small constant additive stretch. We use our stretch 2 distance oracle to present the first compact routing scheme with worst-case stretch 2. Any compact routing scheme with stretch less than 2 must require linear memory at some nodes even for sparse graphs; our scheme, hence, achieves the optimal stretch with non-trivial memory requirements. Moreover, supported by large-scale simulations on graphs including the AS-level Internet graph, we argue that our stretch-2 scheme would be simple and efficient to implement as a distributed compact routing protocol.

cs.DS↗
arXiv2011

On the Expected Complexity of Voronoi Diagrams on Terrains

We investigate the combinatorial complexity of geodesic Voronoi diagrams on polyhedral terrains using a probabilistic analysis. Aronov etal [ABT08] prove that, if one makes certain realistic input assumptions on the terrain, this complexity is Θ(n + m \sqrt n) in the worst case, where n denotes the number of triangles that define the terrain and m denotes the number of Voronoi sites. We prove that under a relaxed set of assumptions the Voronoi diagram has expected complexity O(n+m), given that the sites have a uniform distribution on the domain of the terrain(or the surface of the terrain). Furthermore, we present a worst-case construction of a terrain which implies a lower bound of Vmega(n m2/3) on the expected worst-case complexity if these assumptions on the terrain are dropped. As an additional result, we can show that the expected fatness of a cell in a random planar Voronoi diagram is bounded by a constant.

cs.CG↗
arXiv2011

Geometric Packing under Non-uniform Constraints

We study the problem of discrete geometric packing. Here, given weighted regions (say in the plane) and points (with capacities), one has to pick a maximum weight subset of the regions such that no point is covered more than its capacity. We provide a general framework and an algorithm for approximating the optimal solution for packing in hypergraphs arising out of such geometric settings. Using this framework we get a flotilla of results on this problem (and also on its dual, where one wants to pick a maximum weight subset of the points when the regions have capacities). For example, for the case of fat triangles of similar size, we show an O(1)-approximation and prove that no \PTAS is possible.

cs.CG↗
arXiv2011

On the Expected Complexity of Random Convex Hulls

In this paper we present several results on the expected complexity of a convex hull of $n$ points chosen uniformly and independently from a convex shape. (i) We show that the expected number of vertices of the convex hull of $n$ points, chosen uniformly and independently from a disk is $O(n^{1/3})$, and $O(k \log{n})$ for the case a convex polygon with $k$ sides. Those results are well known (see \cite{rs-udkhv-63,r-slcdn-70,ps-cgi-85}), but we believe that the elementary proof given here are simpler and more intuitive. (ii) Let $\D$ be a set of directions in the plane, we define a generalized notion of convexity induced by $\D$, which extends both rectilinear convexity and standard convexity. We prove that the expected complexity of the $\D$-convex hull of a set of $n$ points, chosen uniformly and independently from a disk, is $O(n^{1/3} + \sqrt{nα(\D)})$, where $α(\D)$ is the largest angle between two consecutive vectors in $\D$. This result extends the known bounds for the cases of rectilinear and standard convexity. (iii) Let $\B$ be an axis parallel hypercube in $\Re^d$. We prove that the expected number of points on the boundary of the quadrant hull of a set $S$ of $n$ points, chosen uniformly and independently from $\B$ is $O(\log^{d-1}n)$. Quadrant hull of a set of points is an extension of rectilinear convexity to higher dimensions. In particular, this number is larger than the number of maxima in $S$, and is also larger than the number of points of $S$ that are vertices of the convex hull of $S$. Those bounds are known \cite{bkst-anmsv-78}, but we believe the new proof is simpler.

cs.CG↗
arXiv2011

Computing the Fréchet Distance Between Folded Polygons

Computing the Fréchet distance for surfaces is a surprisingly hard problem and the only known algorithm is limited to computing it between flat surfaces. We adapt this algorithm to create one for computing the Fréchet distance for a class of non-flat surfaces which we call folded polygons. Unfortunately, the original algorithm cannot be extended directly. We present three different methods to adapt it. The first of which is a fixed-parameter tractable algorithm. The second is a polynomial-time approximation algorithm. Finally, we present a restricted class of folded polygons for which we can compute the Fréchet distance in polynomial time.

cs.CG↗
arXiv2011

Approximation Algorithms for Maximum Independent Set of Pseudo-Disks

We present approximation algorithms for maximum independent set of pseudo-disks in the plane, both in the weighted and unweighted cases. For the unweighted case, we prove that a local search algorithm yields a \PTAS. For the weighted case, we suggest a novel rounding scheme based on an \LP relaxation of the problem, which leads to a constant-factor approximation. Most previous algorithms for maximum independent set (in geometric settings) relied on packing arguments that are not applicable in this case. As such, the analysis of both algorithms requires some new combinatorial ideas, which we believe to be of independent interest.

cs.CG↗
arXiv2010

Relative $(p,ε)$-Approximations in Geometry

We re-examine the notion of relative $(p,\eps)$-approximations, recently introduced in [CKMS06], and establish upper bounds on their size, in general range spaces of finite VC-dimension, using the sampling theory developed in [LLS01] and in several earlier studies [Pol86, Hau92, Tal94]. We also survey the different notions of sampling, used in computational geometry, learning, and other areas, and show how they relate to each other. We then give constructions of smaller-size relative $(p,\eps)$-approximations for range spaces that involve points and halfspaces in two and higher dimensions. The planar construction is based on a new structure--spanning trees with small relative crossing number, which we believe to be of independent interest. Relative $(p,\eps)$-approximations arise in several geometric problems, such as approximate range counting, and we apply our new structures to obtain efficient solutions for approximate range counting in three dimensions. We also present a simple solution for the planar case.

cs.CG↗
arXiv2009

On the Set Multi-Cover Problem in Geometric Settings

We consider the set multi-cover problem in geometric settings. Given a set of points P and a collection of geometric shapes (or sets) F, we wish to find a minimum cardinality subset of F such that each point p in P is covered by (contained in) at least d(p) sets. Here d(p) is an integer demand (requirement) for p. When the demands d(p)=1 for all p, this is the standard set cover problem. The set cover problem in geometric settings admits an approximation ratio that is better than that for the general version. In this paper, we show that similar improvements can be obtained for the multi-cover problem as well. In particular, we obtain an O(log Opt) approximation for set systems of bounded VC-dimension, where Opt is the cardinality of an optimal solution, and an O(1) approximation for covering points by half-spaces in three dimensions and for some other classes of shapes.

cs.CG↗
arXiv2009

Being Fat and Friendly is Not Enough

We show that there is no $(1+\eps)$-approximation algorithm for the problem of covering points in the plane by minimum number of fat triangles of similar size (with the minimum angle of the triangles being close to 45 degrees). Here, the available triangles are prespecified in advance. Since a constant factor approximation algorithm is known for this problem \cite{cv-iaags-07}, this settles the approximability of this problem. We also investigate some related problems, including cover by friendly fat shapes, and independent set of triangles in three dimensions.

cs.CG↗
arXiv2009

Approximating Spanning Trees with Low Crossing Number

We present a linear programming based algorithm for computing a spanning tree $T$ of a set $P$ of $n$ points in $\Re^d$, such that its crossing number is $O(\min(t \log n, n^{1-1/d}))$, where $t$ the minimum crossing number of any spanning tree of $P$. This is the first guaranteed approximation algorithm for this problem. We provide a similar approximation algorithm for the more general settings of building a spanning tree for a set system with bounded \VC dimension. Our approach is an alternative to the reweighting technique previously used in computing such spanning trees. Our approach is an alternative to the reweighting technique previously used in computing such spanning trees.

cs.CG↗
arXiv2008

Range Medians

We study a generalization of the classical median finding problem to batched query case: given an array of unsorted $n$ items and $k$ (not necessarily disjoint) intervals in the array, the goal is to determine the median in {\em each} of the intervals in the array. We give an algorithm that uses $O(n\log n + k\log k \log n)$ comparisons and show a lower bound of $Ω(n\log k)$ comparisons for this problem. This is optimal for $k=O(n/\log n)$.

cs.DS↗