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On the Complexity of Testing Hypermetric, Negative Type, kGonal And Gap Inequalities
 DISCRETE AND COMPUTATIONAL GEOMETRY. LECTURE NOTES IN COMPUTER SCIENCE
, 2003
"... Hypermetric inequalities have many applications, most recently in the approximate solution of maxcut problems by linear and semidefinite programming. However, not much is known about the separation problem for these inequalities. Previously Avis and Grishukhin showed that certain special cases o ..."
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Cited by 4 (0 self)
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in polynomial time. We also show similar results hold for the more general kgonal and gap inequalities.
Spectrum estimation and harmonic analysis
, 1982
"... AbstmctIn the choice of an eduutor for the spectnrm of a ation ..."
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Cited by 438 (3 self)
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AbstmctIn the choice of an eduutor for the spectnrm of a ation
The Unique Games Conjecture, integrality gap for cut problems and embeddability of negative type metrics into `1
 In Proc. 46th IEEE Symp. on Foundations of Comp. Sci
, 2005
"... In this paper we disprove the following conjecture due to Goemans [17] and Linial [25] (also see [5, 27]): “Every negative type metric embeds into `1 with constant distortion. ” We show that for every δ> 0, and for large enough n, there is an npoint negative type metric which requires distortion ..."
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Cited by 180 (13 self)
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In this paper we disprove the following conjecture due to Goemans [17] and Linial [25] (also see [5, 27]): “Every negative type metric embeds into `1 with constant distortion. ” We show that for every δ> 0, and for large enough n, there is an npoint negative type metric which requires
Forecasting and Conditional Projection Using Realistic Prior Distributions,Econometric Review
, 1984
"... in Economic Fluctuations. Any opinions expressed are those of the ..."
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Cited by 288 (7 self)
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in Economic Fluctuations. Any opinions expressed are those of the
Stronger Linear Programming Relaxations of MaxCut
 Mathematical Programming
, 2002
"... We consider linear programming relaxations for the max cut problem in graphs, based on k gonal inequalities. We show that the integrality ratio for random dense graphs is asymptotically 1 + 1=k and for random sparse graphs is at least 1 + 3=k. There are O(n ) kgonal inequalities. These results ..."
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Cited by 9 (1 self)
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We consider linear programming relaxations for the max cut problem in graphs, based on k gonal inequalities. We show that the integrality ratio for random dense graphs is asymptotically 1 + 1=k and for random sparse graphs is at least 1 + 3=k. There are O(n ) kgonal inequalities. These results
Hadamard matrices, sequences, and block designs
 SONS, WILEYINTERSCIENCE SERIES IN DISCRETE MATHEMATICS AND OPTIMIZATION
, 1992
"... One hundred years ago, in 1893, Jacques Hadamard [31] found square matrices of orders 12 and 20, with entries ±1, which had all their rows (and columns) pairwise orthogonal. These matrices, X = (Xij), satisfied the equality of the following inequality, detX2 ≤ ∏ ∑ xij2, and so had maximal dete ..."
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Cited by 111 (36 self)
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One hundred years ago, in 1893, Jacques Hadamard [31] found square matrices of orders 12 and 20, with entries ±1, which had all their rows (and columns) pairwise orthogonal. These matrices, X = (Xij), satisfied the equality of the following inequality, detX2 ≤ ∏ ∑ xij2, and so had maximal
Binary Positive Semidefinite Matrices and Associated Integer Polytopes
"... Abstract. We consider the positive semidefinite (psd) matrices with binary entries. We give a characterisation of such matrices, along with a graphical representation. We then move on to consider the associated integer polytopes. Several important and wellknown integer polytopes — the cut, boolean ..."
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question in the literature on the maxcut problem, by showing that the socalled kgonal inequalities define a polytope. Key Words: polyhedral combinatorics, semidefinite programming. 1
BOUNDING THE TRELLIS STATE COMPLEXITY OF ALGEBRAIC GEOMETRIC CODES
"... Abstract. Let C be an algebraic geometric code of dimension k and length n constructed on a curve X over Fq. Let s(C) be the state complexity of C and set w(C): = min{k, n−k}, the Wolf upper bound on s(C). We introduce a numerical function R that depends on the gonality sequence of X and show that s ..."
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Abstract. Let C be an algebraic geometric code of dimension k and length n constructed on a curve X over Fq. Let s(C) be the state complexity of C and set w(C): = min{k, n−k}, the Wolf upper bound on s(C). We introduce a numerical function R that depends on the gonality sequence of X and show
Results 1  10
of
869