A Novel Model of Working Set Selection for SMO Decomposition Methods

In the process of training Support Vector Machines (SVMs) by decomposition methods, working set selection is an important technique, and some exciting schemes were employed into this field. To improve working set selection, we propose a new model for working set selection in sequential minimal optimization (SMO) decomposition methods. In this model, it selects B as working set without reselection. Some properties are given by simple proof, and experiments demonstrate that the proposed method is in general faster than existing methods.Comment: 8 pages, 12 figures, it was submitted to IEEE International conference of Tools on Artificial Intelligenc

Dimension minimization of a quantum automaton

A new model of a Quantum Automaton (QA), working with qubits is proposed. The quantum states of the automaton can be pure or mixed and are represented by density operators. This is the appropriated approach to deal with measurements and dechorence. The linearity of a QA and of the partial trace super-operator, combined with the properties of invariant subspaces under unitary transformations, are used to minimize the dimension of the automaton and, consequently, the number of its working qubits. The results here developed are valid wether the state set of the QA is finite or not. There are two main results in this paper: 1) We show that the dimension reduction is possible whenever the unitary transformations, associated to each letter of the input alphabet, obey a set of conditions. 2) We develop an algorithm to find out the equivalent minimal QA and prove that its complexity is polynomial in its dimension and in the size of the input alphabet.Comment: 26 page

Global and uniqueness properties of stationary and static spacetimes with outer trapped surfaces

Global properties of maximal future Cauchy developments of stationary, m-dimensional asymptotically flat initial data with an outer trapped boundary are analyzed. We prove that, whenever the matter model is well posed and satisfies the null energy condition, the future Cauchy development of the data is a black hole spacetime. More specifically, we show that the future Killing development of the exterior of a sufficiently large sphere in the initial data set can be isometrically embedded in the maximal Cauchy development of the data. In the static setting we prove, by working directly on the initial data set, that all Killing prehorizons are embedded whenever the initial data set has an outer trapped boundary and satisfies the null energy condition. By combining both results we prove a uniqueness theorem for static initial data sets with outer trapped boundary.Comment: 38 pages, 2 figures, Late

Dynamic Factor Price Equalization & International Convergence

We offer a duality-based methodology for incorporating multi-sector effects of international trade into open economy macroeconomic models, developing the concepts of the dynamic factor price equalization set and the integrated intertemporal equilibrium. Under this approach, the aggregate production function depends on output prices and factor endowment stocks. It preserves all of the structure of a standard GDP function from the trade theory literature. In a two-country version of the model considered below, we examine the properties of the dynamic factor price equalization set. If the global economy is initially outside of this set, the equations of motion will pull the economy back into this set. Inside the dynamic FPE set, factor prices are equalized internationally, and with identical tastes and technology, the economy can be regarded as a fully integrated world equilibrium in a dynamic sense (the integrated intertemporal equilibrium). In this equilibrium, all of the standard properties of a closed economy one-sector neoclassical growth model hold, ruling out cycles and chaos, and allowing us to characterize the evolution of international inequality and the persistence of productivity and endowment shocks. Working from the integrated intertemporal equilibrium, we identify properties of persistence linked to inequality and real economic shocks. Cross-country differences in per capita incomes and wealth, and the factor content of trading patterns, may persist over time and even into the new steady state. This provides yet another reason why we might observe lack of income convergence internationally. In addition, real shocks in one country may be transmitted to the other country through factor markets and product prices, and may have persistent effects into the steady-state as well. The model can also generate an endogenous Balassa-Samuelson effect.Neoclassical Models of Trade, Economic Growth of Open Economies, Cross- Country Output Convergence

Architecture-Driven Semantic Analysis of Embedded Systems (Eds) Dagstuhl Seminar 12272

Architectural modeling of complex embedded systems is gaining prominence in recent years, both in academia and in industry. An architectural model represents components in a distributed system as boxes with well-defined interfaces, connections between ports on component interfaces, and specifies component properties that can be used in analytical reasoning about the model. Models are hierarchically organized, so that each box can contain another system inside, with its own set of boxes and connections between them. The goal of Dagstuhl Seminar 12272 “Architecture-Driven Semantic Analysis of Embedded Systems” is to bring together researchers who are interested in defining precise semantics of an architecture description language and using it for building tools that generate analytical models from architectural ones, as well as generate code and configuration scripts for the system. This report documents the program and the outcomes of the presentations and working groups held during the seminar

Senior activity rate, retirement incentives and labor relations

How is it that populations react so differently to policy incentives among developed countries? We noticed that senior employment rates not only differ in level strikingly from one country to another, they also differ in their reaction to retirement incentives set by governments. We show the importance of trust given to the employer in wage negotiations by a simple trade-off model. According to this model, reaction of the senior activity rate to policy changes depends on the properties of the distribution of trust to employers at the country level. We then identify these properties by an empirical study based on panel data for nineteen OECD countries from 1980 to 2004. We show that the elasticity of senior males labor force participation rate to retirement incentives is stronger in countries with better and more homogeneously distributed working conditions. This results also applies to countries with higher generalized trust.early retirement incentives ; labor relations ; seniors activity rate ; trust

Learning-based predictive control for linear systems: a unitary approach

A comprehensive approach addressing identification and control for learningbased Model Predictive Control (MPC) for linear systems is presented. The design technique yields a data-driven MPC law, based on a dataset collected from the working plant. The method is indirect, i.e. it relies on a model learning phase and a model-based control design one, devised in an integrated manner. In the model learning phase, a twofold outcome is achieved: first, different optimal p-steps ahead prediction models are obtained, to be used in the MPC cost function; secondly, a perturbed state-space model is derived, to be used for robust constraint satisfaction. Resorting to Set Membership techniques, a characterization of the bounded model uncertainties is obtained, which is a key feature for a successful application of the robust control algorithm. In the control design phase, a robust MPC law is proposed, able to track piece-wise constant reference signals, with guaranteed recursive feasibility and convergence properties. The controller embeds multistep predictors in the cost function, it ensures robust constraints satisfaction thanks to the learnt uncertainty model, and it can deal with possibly unfeasible reference values. The proposed approach is finally tested in a numerical example