We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
: Performance modeling for scientific production codes is of interest both for program tuning and for the selection of new machines. An empirical method is used for developing a m...
Abstract. We present a new generic problem solving approach for overconstrained problems based on Max-SAT. We first define a clausal form formalism that deals with blocks of clau...