Mini-max algorithm via Pohozaev manifold

A Genetic Algorithm for the Mini-Max Spanning Forest Problem

Consider an election of r seats in country consisting of r cities and several villages. The problem is to divide the country into r electoral districts in such a way that each district consists of a city and some villages which are not separated by other districts. The total population of each district must be as balanced as possible. Generally, as each district can be regarded as the nodes on ...

Computing Linear Mini-max Estimators

Consider a vector of data y = + "; y 2 IR n , where " = (" i) 1in is an error vector which satisses the "usual\ conditions, and 2 IR n. The problem is to nd/compute a vector m for which hm;yi minimizes the maximal risk among all linear estimators, i.e. m is a solution of min m2IR n max 2 E h`;i ? hm;i 2 , ` 2 IR n given. A solution of this mini-max problem is determined by the solution of the f...

Mini-max initialization for function approximation

Neural networks have been successfully applied to various pattern recognition and function approximation problems. However, the training process remains a time-consuming procedure that often gets stuck in a local minimum. The optimum network size and topology are usually unknown. In this paper, we formulate the concept of extrema equivalence for estimating the complexity of a function. Based on...

Sampling methods for Mini-Max Action Identification

Using Mini-Bucket Heuristics for Max-CSP

This paper evaluates the power of a new scheme that generates search heuristics mechanically. This approach was presented and evaluated rst in the context of optimization in belief networks. In this paper we extend this work to Max-CSP. The approach involves extracting heuristics from a parameterized approximation scheme called Mini-Bucket elimination that allows controlled trade-o between comp...