Many classification problems have in fact an ordinal nature, i.e., the class labels are ordered. We introduce a decision rule algorithm, called RankRules, tailored for this type of problems, that is based on minimization of the rank loss. In general, the complexity of the rank loss minimization is quadratic with respect to the number of training examples, however, we show that the introduced al...

Regularized risk minimization with the binary hinge loss and its variants lies at the heart of many machine learning problems. Bundle methods for regularized risk minimization (BMRM) and the closely related SVMStruct are considered the best general purpose solvers to tackle this problem. It was recently shown that BMRM requires O(1/ε) iterations to converge to an ε accurate solution. In the fir...

simultaneous routing and resource allocation has been considered in wireless networks for its performance improvement. in this paper we propose a cross-layer optimization framework for worst-case queue length minimization in some type of fdma based wireless networks, in which the the data routing and the power allocation problem are jointly optimized with fuzzy distributed h∞ control strategy ....