118 research outputs found
Kinstate intervention in ethnic conflicts : Albania and Turkey compared
No full textAlbania and Turkey did not act in overtly irredentist ways towards their ethnic brethren in neighboring states after the end of communism. Why, nonetheless, did Albania facilitate the increase of ethnic conflict in Kosovo and Macedonia, while Turkey did not, with respect to the Turks of Bulgaria? I argue that kin-states undergoing transition are more prone to intervene in external conflicts than states that are not, regardless of the salience of minority demands in the host-state. The transition weakens the institutions of the kin-state. Experiencing limited institutional constraints, self-seeking state officials create alliances with secessionist and autonomist movements across borders alongside their own ideological, clan-based and particularistic interests. Such alliances are often utilized to advance radical domestic agendas. Unlike in Albania's transition environment, in Turkey there were no emerging elites that could potentially form alliances and use external movements to legitimize their own domestic existence or claims
Large-scale robust transductive support vector machines
No full textIn this paper, we propose a robust and fast transductive support vector machine (RTSVM) classifier that can be applied to large-scale data. To this end, we use the robust Ramp loss instead of Hinge loss for labeled data samples. The resulting optimization problem is non-convex but it can be decomposed to a convex and concave parts. Therefore, the optimization is accomplished iteratively by solving a sequence of convex problems known as concave-convex procedure. Stochastic gradient (SG) is used to solve the convex problem at each iteration, thus the proposed method scales well with large training set size for the linear case (to the best of our knowledge, it is the second transductive classification method that is practical for more than a million data). To extend the proposed method to the nonlinear case, we proposed two alternatives where one uses the primal optimization problem and the other uses the dual. But in contrast to the linear case, both alternatives do not scale well with large-scale data. Experimental results show that the proposed method achieves comparable results to other related transductive SVM methods, but it is faster than other transductive learning methods and it is more robust to the noisy data
Training Set Approximation for Kernel Methods
No full textWe propose a technique for a training set approximation and its usage in kernel methods. The approach aims to represent data in a low dimensional space with possibly minimal representation error which is similar to the Principal Component Analysis (PCA). In contrast to the PCA, the basis vectors of the low dimensional space used for data representation are properly selected vectors from the training set and not as their linear combinations. The basis vectors can be selected by a simple algorithm which has low computational requirements and allows on-line processing of huge data sets. The proposed method was used to approximate training sets of the Support Vector Machines and Kernel Fisher Linear Discriminant which are known method for learning classifiers. The experiments show that the proposed approximation can significantly reduce the complexity of the found classifiers (the number of the support vectors) while retaining their accuracy
Multi-class Support Vector Machine
No full textclassification problem to the single-class SVM problem which is more convenient for optimization. The proposed transformation is based on simplifying the original problem and employing the Kesler construction which can be carried out by the use of properly defined kernel only. The experiments conducted indicate that the proposed method is comparable with the one-against-all decomposition solved by the state-of-the-art SMO algorithm
Monetary Policy of the Federal Reserve System in 2007-2010
No full textThe thesis describes the chain of causation that leads from the causes of the financial crisis over its consequencies towards the reactions of the Federal Reserve System. After the consequencies of the Crisis have been identified, the author deals in detail with the measures taken -- with their characteristics and the way they function. Afterwards, the author evaluates efficiency of these meausures and describes the role they played in the overall attitude of the Federal Reserve System to handling the Crisis
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