We propose to tackle the cost-sensitive learning problem, where each feature is associated to a particular acquisition cost. We propose a new model with the following key properties: (i) it acquires features in an adaptive way, (ii) features can be acquired per block (several at a time) so that this model can deal with high dimensional data, and (iii) it relies on representation-learning ideas....

Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs have been used in cost-sensitive learning because of the ease with which class skew and error cost information can be applied to them to yield cost-sensitive decisions. However, they have been criticized because of their inability to handle instance-var...

This paper proposes an effective and novel multi-agent deep reinforcement learning (MADRL)-based method for solving the joint virtual network function (VNF) placement routing (P&R), where multiple service requests with differentiated demands are delivered at same time. The of reflected by their delay- cost-sensitive factors. We first construct a VNF P&R problem to jointly minimize weighted sum ...

he empirical studies have shown that cost advantages can occur due to economies of scale and economies of learning. However, a few studies have attempted to distinguish between these two effects on reducing costs. This paper is the first attempt on recognizing the impact of learning on reducing the cost with distinguishing the effect of economies of scale in Iran. Therefore, this study aims to ...

a r t i c l e i n f o Keywords: Cost-sensitive regression Model trees Evolutionary algorithms Asymmetric costs Loan charge-off forecasting Regression learning methods in real world applications often require cost minimization instead of the reduction of various metrics of prediction errors. Currently in the literature, there is a lack of white box solutions that can deal with forecasting proble...

common spatial pattern (csp) is a method commonly used to enhance the effects of event‑related desynchronization and event‑related synchronization present in multichannel electroencephalogram‑based brain‑computer interface (bci) systems. in the present study, a novel csp sub‑band feature selection has been proposed based on the discriminative information of the features. besides, a distinction ...