The multiple knapsack problem with grouped items aims to maximize rewards by assigning groups of among knapsacks, without exceeding capacities. Either all in a group are assigned or none at all. We study the bi-criteria variation problem, where capacities can be exceeded and second objective is minimize maximum capacity. propose approximation algorithms that run pseudo-polynomial time guarantee...

A technique is presented that allows one to store groups of properties in C++, and single properties out of these groups can later be accessed by their name. Our approach refines previous work in this area and is an example for the application of template metaprogramming [1]. Typical usage examples of the introduced class templates are internal representations of serialized data, well suited fo...

We study the problem of multivariate regression where the data are naturally grouped, and a regression matrix is to be estimated for each group. We propose an approach in which a dictionary of low rank parameter matrices is estimated across groups, and a sparse linear combination of the dictionary elements is estimated to form a model within each group. We refer to the method as conditional spa...

We address the problem of recovering a common set of covariates that are relevant simultaneously to several classification problems. We propose a joint measure of complexity for the group of problems that couples covariate selection. By penalizing the sum of `2-norms of the blocks of coefficients associated with each covariate across different classification problems, we encourage similar spars...

background and purpose: consideringbackground and purpose: considering the importance and necessity of competency-based education at a global level and with respect to globalization and the requirement of minimum competencies in medical fields, medical education communities and organizations worldwide have tried to determine the competencies, present frameworks and education models to respond t...