We discuss a generalisation of the approximate optimal experimental design problem, in which weight each regression point needs to stay closed interval. work with Kiefer’s optimality criteria include well-known D- and A-optimality as special cases. propose first-order algorithm for generalised problem that redistributes weights two points iteration. develop branch-and-bound exact problems under...

Abstract Since its introduction in the early 2000s, robust optimization with budget uncertainty has received a lot of attention. This is due to intuitive construction sets and existence compact reformulation for (mixed-integer) linear programs. However, despite compactness, performs poorly when solving integer problems weak relaxation. To overcome arising from formulation, we propose bilinear f...

We introduce a novel algorithm for optimal feature selection As op posed to our recent Fast Branch Bound FBB algorithm the new algorithm is well suitable for use with recursive criterion forms Even if the new algorithm does not operate as e ectively as the FBB algorithm it is able to nd the optimum signi cantly faster than any other Branch Bound algorithm