We address the problem of multi-task learning with no label correspondence among tasks. Learning multiple related tasks simultaneously, by exploiting their shared knowledge can improve the predictive performance on every task. We develop the multi-task Adaboost environment with Multi-Task Decision Trees as weak classifiers. We first adapt the well known decision tree learning to the multi-task ...

In the construction management planning, both client and contractor are interested in completing project within planned schedule. To achieve it, time-cost trade-off problem (TCTP) is carried-out to obtain optimal set of alternatives. Although Pareto front solutions not preferred each other, decision-maker (DM) has choose only best solution. The DMs neither well-educated nor have adequate knowle...

Determining the weights of assets in a portfolio is one fundamental problems finance. MCDM techniques are employed for asset allocation purposes. However, criterion have to be determined before steps implemented. In this study, criteria by four different weight (CILOS, CRITIC, MEREC, and SECA), effect these on performance portfolios created with 17 (ARAS, CoCoSo, CODAS, COPRAS, EDAS, GRA, MABAC...

An effective approach to decision support in multicriteria decision making (MCDM) problems characterized by three to eight decision criteria is described. The approach is based on approximating the feasible set in the criterion space (or a broader criterion set, which has the same Pareto frontier) and visualization of the Pareto frontier by interactive displaying bi-criterion slices of this set...