Advantages and limitations of the existing volatility models for forecasting foreign-exchange and stock market volatility from multiscale and high-dimensional data have been identi/ed. Support vector machines (SVM) have been proposed as a complimentary volatility model that is capable of e0ectively extracting information from multiscale and high-dimensional market data. SVM-based models can han...

In this article, we propose a novel application for Support Vector Regression (SVR) for strategies of executing orders on stock exchanges. We use SVR for predicting volume participation function in execution strategies which try to achieve Volume Weighted Average Price (VWAP) measure of quality of the execution. Moreover, we use SVR with a priori knowledge about stock prices in order to further...

The problem of ranking is to predict or to guess the ordering between objects on the basis of their observed features. In this paper we consider ranking estimators that minimize the empirical convex risk. We prove generalization bounds for the excess risk of such estimators with rates that are faster than 1 √n . We apply our results to commonly used ranking algorithms, for instance boosting or ...

This paper presents a geometric approach to recognizing smooth objects from their outlines. We define a signature function that associates feature vectors with objects and baselines connecting pairs of possible viewpoints. Feature vectors, which can be projective, affine, or Euclidean, are computed using the planes that pass through a fixed baseline and are also tangent to the object’s surface....

The paper addresses the problem of extracting acronyms and their expansions from text. We propose a support vector machines (SVM) based approach to deal with the problem. First, all likely acronyms are identified using heuristic rules. Second, expansion candidates are generated from surrounding text of acronyms. Last, SVM model is employed to select the genuine expansions. Analysis shows that t...

In this paper we present efficient algorithmic solutions for several constrained resource allocation, management and discovery problems. We consider new types of resource allocation models and constraints, and we present new geometric techniques which are useful when the resources are mapped to points into a multidimensional feature space. We also consider a resource discovery problem for which...

Ontologies, which are made up by standardized and defined controlled vocabulary terms and their interrelationships, are comprehensive and readily searchable repositories for knowledge in a given domain. The Open Biomedical Ontologies (OBO) Foundry was initiated in 2001 with the aims of becoming an "umbrella" for life-science ontologies and promoting the use of ontology development best practice...

This paper describes a domain independent, automatically trained call router which directs customer calls based on their response to an open-ended "How may ldirect your call?" query. Routing behavior is trained from a corpus of transcribed and handorouted calls and then carried out using vector-based information retrieval techniques. Based on the statistical discriminating power of the n-gram t...

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