Since introduction, the Support Vector Machines (SVM) has been popularly used in machine learning and data mining tasks due to their strong mathematical background and promising result. Nevertheless, they are noticeably slow in the prediction stage. The speed is influenced by number of support vectors determined in the training phase. Motivated by this fact, several studies are done to reduce t...

We present three ways of combining linear programming with the kernel trick to find value function approximations for reinforcement learning. One formulation is based on SVM regression; the second is based on the Bellman equation; and the third seeks only to ensure that good moves have an advantage over bad moves. All formulations attempt to minimize the number of support vectors while fitting ...

results the data revealed that self-efficacy (p < 0.001) and social support (p < 0.001) are indicators than can significantly anticipate levels of adjustment in diabetic patients. moreover, it has been revealed that self-efficiency plays a significant and, indeed, fundamental role in adjustment anticipation. conclusions it can be concluded that self-efficacy and social support are important in ...

Pressure support ventilation (PSV) is a pressure assist form of mechanical ventilatory support that augments the patient's spontaneous inspiratory efforts with a clinician selected level of positive airway pressure. To understand the effects of PSV on respiratory function, experiments were performed on 15 stable patients requiring synchronized intermittent mandatory ventilation (SIMV), as well ...

In this paper, we present a decision support system based on belief functions and the pignistic transformation. The system is an integration of an evidential system for belief function propagation and a valuation-based system for Bayesian decision analysis. The two subsystems are connected through the pignistic transformation. The system takes as inputs the user's "gut feelings" about a situati...

There exists a vast literature about the di erentiabil ity of fuzzy valued mappings see for instance Dubois and Prade Puri and Ralescu Goetschel and Voxman or Kaleva One of the main problems in working with di erentials of fuzzy valued mappings is that the usual class of fuzzy sets of R does not con gure a vectorial space with respect to the sum and the product by a scalar induced by Zadeh s Ex...

‎Many optimization problems can be reduced to a problem with an increasing and co-radiant objective function by a suitable transformation of variables. Functions, which are increasing and co-radiant, have found many applications in microeconomic analysis. In this paper, the abstract convexity of positive valued affine increasing and co-radiant (ICR) functions are discussed. Moreover, the ...