We show that for k ≥ 3 even the Ω(n) level of the Lasserre hierarchy cannot disprove a random k-CSP instance over any predicate type implied by k-XOR constraints, for example k-SAT or k-XOR. (One constant is said to imply another if the latter is true whenever the former is. For example k-XOR constraints imply k-CNF constraints.) As a result the Ω(n) level Lasserre relaxation fails to approximate such CSPs better than the trivial, random algorithm. As corollaries, we obtain Ω(n) level integrality gaps for the Lasserre hierarchy of 76 − ε for Ver-texCover, 2 − ε for k-UniformHypergraphVertexCover, and any constant for k-UniformHypergraphIndependentSet. This is the first construction of a Lasserre inte-grality gap. Our construction is notable...
This paper analyzes the relation between different orders of the Lasserre hierarchy for polynomial o...
We prove new bounds on the additive gap between the value of a random integer program $\max c^Tx,\ A...
The matrix cuts of Lovász and Schrijver are methods for tightening linear relaxations of zero-one p...
We show that the ellipsoid method for solving semidefinite programs (SDPs) can be expressed in fixed...
The Lasserre hierarchy is a systematic procedure for constructing a sequence of increas-ingly tight ...
Partitioning the vertices of a graph into two roughly equal parts while minimizing the number of edg...
The inapproximability for NP-hard combinatorial optimization problems lies in the heart of theoretic...
Constraint Satisfaction Problems (CSPs) are a class of fundamental combinatorial optimization proble...
Abstract. Partitioning the vertices of a graph into two roughly equal parts while minimizing the num...
Partitioning the vertices of a graph into two roughly equal parts while minimizing the number of edg...
It has been shown that for a general-valued constraint language Γ the following statements are equiv...
We show that linear programming relaxations need sub-exponential size to beat trivial random guessin...
We study the approximability of constraint satisfaction problems (CSPs) by linear programming (LP) r...
Studying the approximation threshold of NP-hard optimization problems, i.e. the ratio of the objecti...
We study the approximability of constraint satisfaction problems (CSPs) by linear programming (LP) r...
This paper analyzes the relation between different orders of the Lasserre hierarchy for polynomial o...
We prove new bounds on the additive gap between the value of a random integer program $\max c^Tx,\ A...
The matrix cuts of Lovász and Schrijver are methods for tightening linear relaxations of zero-one p...
We show that the ellipsoid method for solving semidefinite programs (SDPs) can be expressed in fixed...
The Lasserre hierarchy is a systematic procedure for constructing a sequence of increas-ingly tight ...
Partitioning the vertices of a graph into two roughly equal parts while minimizing the number of edg...
The inapproximability for NP-hard combinatorial optimization problems lies in the heart of theoretic...
Constraint Satisfaction Problems (CSPs) are a class of fundamental combinatorial optimization proble...
Abstract. Partitioning the vertices of a graph into two roughly equal parts while minimizing the num...
Partitioning the vertices of a graph into two roughly equal parts while minimizing the number of edg...
It has been shown that for a general-valued constraint language Γ the following statements are equiv...
We show that linear programming relaxations need sub-exponential size to beat trivial random guessin...
We study the approximability of constraint satisfaction problems (CSPs) by linear programming (LP) r...
Studying the approximation threshold of NP-hard optimization problems, i.e. the ratio of the objecti...
We study the approximability of constraint satisfaction problems (CSPs) by linear programming (LP) r...
This paper analyzes the relation between different orders of the Lasserre hierarchy for polynomial o...
We prove new bounds on the additive gap between the value of a random integer program $\max c^Tx,\ A...
The matrix cuts of Lovász and Schrijver are methods for tightening linear relaxations of zero-one p...