With the fast development of data collection techniques, a huge amount of complex multi-modal data are generated, shared and stored on the Internet. The burden of extracting multi-modal features for test instances in data analysis becomes the main fact that hurts the efficiency of prediction. In this paper, in order to reduce the modal extraction cost in serialized classification system, we pro...

Although initially originated as a totally empirical relationship to explain the volume of trade between two partners, gravity equation has been the focus of several theoretic models that try to explain it. Specialization models are of great importance in providing a solid theoretic ground for gravity equation in bilateral trade. Some research papers try to improve specialization models by addi...

the main purpose of this paper is analyses the short and long run relationship between budget deficit and trade deficit in some mena countries. the data cover the period from 1971-2000 (and for i.r. iran 1 959-2003).the relationship between these variables will be analyses in short and long run by using johansen cointegration tests, ecm, and granger causality test. the empirical evidence provid...

We consider a generic convex-concave saddle point problem with a separable structure, a form that covers a wide-ranged machine learning applications. Under this problem structure, we follow the framework of primal-dual updates for saddle point problems, and incorporate stochastic block coordinate descent with adaptive stepsizes into this framework. We theoretically show that our proposal of ada...

A common approach to statistical learning with Big-data is to randomly split it among m machines and learn the parameter of interest by averaging the m individual estimates. In this paper, focusing on empirical risk minimization or equivalently M-estimation, we study the statistical error incurred by this strategy. We consider two large-sample settings: first, a classical setting where the numb...