An instance of the Constraint Satisfaction Problem (CSP) is given by a family of constraints on overlapping sets of variables, and the goal is to assign values from a fixed domain to the variables so that all constraints are satisfied.
Jul 16, 2016
In this paper, we consider CSPs with a constraint language having a near-unanimity polymorphism. This general condition almost matches a known necessary ...
Jan 4, 2017 · In the optimization version, the goal is to maximize the number of satisfied constraints. An approximation algorithm for CSP is called robust if ...
... robust algorithm with polynomial loss. We give two randomized robust algorithms with polynomial loss for such CSPs: one works for any near-unanimity ...
An instance of the Constraint Satisfaction Problem. (CSP) is given by a family of constraints on over- lapping sets of variables, and the goal is to assign.
Dec 4, 2018 · It seems very hard to obtain a robust algorithm with polynomial loss for every CSP satisfying. SD(∨) all in one step. From the algebraic ...
We study how the robust approximability of CSPs depends on the set of constraint relations allowed in instances, the so-called constraint language. All ...
We study how the robust approximability of CSPs depends on the set of constraint relations allowed in instances, the so-called constraint language. All ...
Two randomized robust algorithms with polynomial loss for CSPs with a constraint language having a near-unanimity polymorphism are given: one works for any ...
In this paper, we consider CSPs with a constraint language having a near-unanimity polymorphism. This general condition almost matches a known necessary ...