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A New Minimax Theorem for Randomized Algorithms
The celebrated minimax principle of Yao says that for any Boolean-valued function f with finite domain, there is a distribution μ over the domain of f such that computing f to error ε against inputs from μ is just as hard as computing f to error ε on ...
Toward a Better Understanding of Randomized Greedy Matching
There has been a long history of studying randomized greedy matching algorithms since the work by Dyer and Frieze [9]. We follow this trend and consider the problem formulated in the oblivious setting, in which the vertex set of a graph is known to the ...
Pliability and Approximating Max-CSPs
We identify a sufficient condition, treewidth-pliability, that gives a polynomial-time algorithm for an arbitrarily good approximation of the optimal value in a large class of Max-2-CSPs parameterised by the class of allowed constraint graphs (with ...