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39
Optimal inapproximability results for MAXCUT and other 2variable CSPs?
, 2005
"... In this paper we show a reduction from the Unique Games problem to the problem of approximating MAXCUT to within a factor of ffGW + ffl, for all ffl> 0; here ffGW ss.878567 denotes the approximation ratio achieved by the GoemansWilliamson algorithm [25]. This implies that if the Unique Games ..."
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Cited by 173 (24 self)
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In this paper we show a reduction from the Unique Games problem to the problem of approximating MAXCUT to within a factor of ffGW + ffl, for all ffl> 0; here ffGW ss.878567 denotes the approximation ratio achieved by the GoemansWilliamson algorithm [25]. This implies that if the Unique Games
Every monotone graph property has a sharp threshold
 Proc. Amer. Math. Soc
, 1996
"... Abstract. In their seminal work which initiated random graph theory Erdös and Rényi discovered that many graph properties have sharp thresholds as the number of vertices tends to infinity. We prove a conjecture of Linial that every monotone graph property has a sharp threshold. This follows from the ..."
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Cited by 130 (15 self)
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Abstract. In their seminal work which initiated random graph theory Erdös and Rényi discovered that many graph properties have sharp thresholds as the number of vertices tends to infinity. We prove a conjecture of Linial that every monotone graph property has a sharp threshold. This follows from the following theorem. Let Vn(p) ={0,1} n denote the Hamming space endowed with the probability measure µp defined by µp(ɛ1,ɛ2,...,ɛn) = pk ·(1 − p) n−k,where k = ɛ1+ ɛ2+ ···+ ɛn. Let A be a monotone subset of Vn. We say that A is symmetric if there is a transitive permutation group Γ on {1, 2,...,n} such that A is invariant under Γ. Theorem. For every symmetric monotone A,ifµp(A)>ɛthen µq(A)> 1−ɛ for q = p + c1 log(1/2ɛ) / log n. (c1isan absolute constant.) 1. Graph properties A graph property is a property of graphs which depends only on their isomorphism class. Let P be a monotone graph property; that is, if a graph G satisfies P
Noise sensitivity of Boolean functions and applications to percolation, Inst. Hautes Études
, 1999
"... It is shown that a large class of events in a product probability space are highly sensitive to noise, in the sense that with high probability, the configuration with an arbitrary small percent of random errors gives almost no prediction whether the event occurs. On the other hand, weighted majority ..."
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Cited by 72 (16 self)
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It is shown that a large class of events in a product probability space are highly sensitive to noise, in the sense that with high probability, the configuration with an arbitrary small percent of random errors gives almost no prediction whether the event occurs. On the other hand, weighted majority functions are shown to be noisestable. Several necessary and sufficient conditions for noise sensitivity and stability are given. Consider, for example, bond percolation on an n + 1 by n grid. A configuration is a function that assigns to every edge the value 0 or 1. Let ω be a random configuration, selected according to the uniform measure. A crossing is a path that joins the left and right sides of the rectangle, and consists entirely of edges e with ω(e) = 1. By duality, the probability for having a crossing is 1/2. Fix an ǫ ∈ (0,1). For each edge e, let ω ′ (e) = ω(e) with probability 1 − ǫ, and ω ′ (e) = 1 − ω(e)
Testing Monotonicity
, 1999
"... We present a (randomized) test for monotonicity of Boolean functions. Namely, given the ability to query an unknown function f : f0; 1g 7! f0; 1g at arguments of its choice, the test always accepts a monotone f , and rejects f with high probability if it is fflfar from being monotone (i.e., e ..."
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Cited by 57 (12 self)
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We present a (randomized) test for monotonicity of Boolean functions. Namely, given the ability to query an unknown function f : f0; 1g 7! f0; 1g at arguments of its choice, the test always accepts a monotone f , and rejects f with high probability if it is fflfar from being monotone (i.e., every monotone function differs from f on more than an ffl fraction of the domain).
The Analysis of a ListColoring Algorithm on a Random Graph (Extended Abstract)
, 1997
"... We introduce a natural kcoloring algorithm and analyze its performance on random graphs with constant expected degree c (Gn,p=c/n). For k = 3 our results imply that almost all graphs with n vertices and 1.923 n edges are 3colorable. This improves the lower bound on the threshold for random 3col ..."
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Cited by 33 (5 self)
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We introduce a natural kcoloring algorithm and analyze its performance on random graphs with constant expected degree c (Gn,p=c/n). For k = 3 our results imply that almost all graphs with n vertices and 1.923 n edges are 3colorable. This improves the lower bound on the threshold for random 3colorability significantly and settles the last case of Q longstanding open question of Bollobas [5]. We also provide a tight asymptotic analysis of the algorithm. We show that for all k 2 3, if c 5 klnk 3/2k then the algorithm almost surely succeeds, while for any E> 0, and k sufficiently large, if c 2 (1 + E)k In k then the algorithm almost surely fails. The analysis is based on the use of differential equations to approximate the mean path of certain Markov chains.
The critical probability for random Voronoi percolation in the plane is 1/2, Probability Theory and Related Fields 136
, 2006
"... We study percolation in the following random environment: let Z be a Poisson process of constant intensity on R 2, and form the Voronoi tessellation of R 2 with respect to Z. Colour each Voronoi cell black with probability p, independently of the other cells. We show that the critical probability is ..."
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Cited by 32 (5 self)
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We study percolation in the following random environment: let Z be a Poisson process of constant intensity on R 2, and form the Voronoi tessellation of R 2 with respect to Z. Colour each Voronoi cell black with probability p, independently of the other cells. We show that the critical probability is 1/2. More precisely, if p> 1/2 then the union of the black cells contains an infinite component with probability 1, while if p < 1/2 then the distribution of the size of the component of black cells containing a given point decays exponentially. These results are analogous to Kesten’s results for bond percolation in Z 2. The result corresponding to Harris ’ Theorem for bond percolation in Z 2 is known: Zvavitch noted that one of the many proofs of this result can easily be adapted to the random Voronoi setting. For Kesten’s results, none of the existing proofs seems to adapt. The methods used here also give a new and very simple proof of Kesten’s Theorem for Z 2; we hope
Influences Of Variables And Threshold Intervals Under Group Symmetries
 Funct. Anal
"... Introduction. A subset A of f0; 1g n is called monotone provided if x 2 A; x 0 2 f0; 1g n ; x i x 0 i for i = 1; : : : ; n then x 0 2 A. For 0 p 1, define p the product measure on f0; 1g n with weights 1 \Gamma p at 0 and p at 1. Thus p (fxg) = (1 \Gamma p) n\Gammaj p j where ..."
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Cited by 28 (9 self)
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Introduction. A subset A of f0; 1g n is called monotone provided if x 2 A; x 0 2 f0; 1g n ; x i x 0 i for i = 1; : : : ; n then x 0 2 A. For 0 p 1, define p the product measure on f0; 1g n with weights 1 \Gamma p at 0 and p at 1. Thus p (fxg) = (1 \Gamma p) n\Gammaj p j where j = #fi = 1; : : : ; njx i = 1g: (0.1) If
First Passage Percolation Has Sublinear Distance Variance
 Ann. Probab
, 1970
"... Let 0 < a < b < ∞, and for each edge e of Z d let ωe = a or ωe = b, each with probability 1/2, independently. This induces a random metric distω on the vertices of Z d, called first passage percolation. We prove that for d> 1 the distance distω(0,v) from the origin to a vertex v, v > 2, has varian ..."
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Cited by 28 (5 self)
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Let 0 < a < b < ∞, and for each edge e of Z d let ωe = a or ωe = b, each with probability 1/2, independently. This induces a random metric distω on the vertices of Z d, called first passage percolation. We prove that for d> 1 the distance distω(0,v) from the origin to a vertex v, v > 2, has variance bounded by C v/log v, where C = C(a,b,d) is a constant which may only depend on a, b and d. Some related variants are also discussed. 1
On the distance distribution of codes
 IEEE Trans. Inform. Theory
, 1995
"... Abstract The dimme drctrrbutron of a binary code C ' is the sequence ..."
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Cited by 27 (1 self)
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Abstract The dimme drctrrbutron of a binary code C ' is the sequence
Negative dependence and the geometry of polynomials
, 2008
"... We introduce the class of strongly Rayleigh probability measures by means of geometric properties of their generating polynomials that amount to the stability of the latter. This class covers important models such as determinantal measures (e.g. product measures, uniform random spanning tree measur ..."
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Cited by 22 (10 self)
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We introduce the class of strongly Rayleigh probability measures by means of geometric properties of their generating polynomials that amount to the stability of the latter. This class covers important models such as determinantal measures (e.g. product measures, uniform random spanning tree measures) and distributions for symmetric exclusion processes. We show that strongly Rayleigh measures enjoy all virtues of negative dependence and we also prove a series of conjectures due to Liggett, Pemantle, and Wagner, respectively. Moreover, we extend Lyons’ recent results on determinantal measures and we construct counterexamples to several conjectures of Pemantle