Locally linear approximation for Kernel methods : the Railway Kernel

In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capability of the proposed kernel is higher than the obtained using RBF kernels. Experimental work is shown to support the theoretical issues

Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification

Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work with (low) finite-dimensional vectors. Within this context we propose techniques to obtain finitedimensional representations of functional data. The key idea is to consider each functional curve as a point in a general function space and then project these points onto a Reproducing Kernel Hilbert Space with the aid of Regularization theory. In this work we describe the projection method, analyze its theoretical properties and propose a model selection procedure to select appropriate Reproducing Kernel Hilbert spaces to project the functional data.Functional data, Reproducing, Kernel Hilbert Spaces, Regularization theory

The resolving number of a graph

We study a graph parameter related to resolving sets and metric dimension, namely the resolving number, introduced by Chartrand, Poisson and Zhang. First, we establish an important difference between the two parameters: while computing the metric dimension of an arbitrary graph is known to be NP-hard, we show that the resolving number can be computed in polynomial time. We then relate the resolving number to classical graph parameters: diameter, girth, clique number, order and maximum degree. With these relations in hand, we characterize the graphs with resolving number 3 extending other studies that provide characterizations for smaller resolving number.Comment: 13 pages, 3 figure

Resolving sets for breaking symmetries of graphs

This paper deals with the maximum value of the difference between the determining number and the metric dimension of a graph as a function of its order. Our technique requires to use locating-dominating sets, and perform an independent study on other functions related to these sets. Thus, we obtain lower and upper bounds on all these functions by means of very diverse tools. Among them are some adequate constructions of graphs, a variant of a classical result in graph domination and a polynomial time algorithm that produces both distinguishing sets and determining sets. Further, we consider specific families of graphs where the restrictions of these functions can be computed. To this end, we utilize two well-known objects in graph theory: $k$-dominating sets and matchings.Comment: 24 pages, 12 figure

Explicit parametric solutions of lattice structures with proper generalized decomposition (PGD): applications to the design of 3D-printed architectured materials

The final publication is available at Springer via http://dx.doi.org/10.1007/s00466-017-1534-9Architectured materials (or metamaterials) are constituted by a unit-cell with a complex structural design repeated periodically forming a bulk material with emergent mechanical properties. One may obtain specific macro-scale (or bulk) properties in the resulting architectured material by properly designing the unit-cell. Typically, this is stated as an optimal design problem in which the parameters describing the shape and mechanical properties of the unit-cell are selected in order to produce the desired bulk characteristics. This is especially pertinent due to the ease manufacturing of these complex structures with 3D printers. The proper generalized decomposition provides explicit parametic solutions of parametric PDEs. Here, the same ideas are used to obtain parametric solutions of the algebraic equations arising from lattice structural models. Once the explicit parametric solution is available, the optimal design problem is a simple post-process. The same strategy is applied in the numerical illustrations, first to a unit-cell (and then homogenized with periodicity conditions), and in a second phase to the complete structure of a lattice material specimen.Peer ReviewedPostprint (author's final draft

Global properties of the spectrum of the Haldane-Shastry spin chain

We derive an exact expression for the partition function of the su(m) Haldane-Shastry spin chain, which we use to study the density of levels and the distribution of the spacing between consecutive levels. Our computations show that when the number of sites N is large enough the level density is Gaussian to a very high degree of approximation. More surprisingly, we also find that the nearest-neighbor spacing distribution is not Poissonian, so that this model departs from the typical behavior for an integrable system. We show that the cumulative spacing distribution of the model can be well approximated by a simple functional law involving only three parameters.Comment: RevTeX 4, 7 pages, 4 figures. To appear in Phys. Rev.

Infrared thermograms applied to near-field testing

Electromagnetic fields close to radiant structures can be measured quickly using an infrared camera. Examples of induced fields by wire antennas over a detection screen at distances shorter than one wavelength are presented. The measured thermograms agree with simulations that take into account heat propagation on the detection screenPeer ReviewedPostprint (published version

Quasi-integration in less-than-truckload trucking

This work studies the organization of less-than-truckload trucking from a contractual point of view. We show that the huge number of owner-operators working in the industry hides a much less fragmented reality. Most of those owner-operators are “quasi-integrated” in higher organizational structures. This hybrid form is generally more efficient than vertical integration because, in the Spanish institutional environment, it lessens serious moral hazard problems, related mainly to the use of the vehicles, and makes it possible to reach economies of scale and density. Empirical evidence suggests that what leads organizations to vertically integrate is not the presence of such economies but hold-up problems, related to the existence of specific assets. Finally, an international comparison hints that institutional constraints are able to explain differences in the evolution of vertical integration across countries.Hold-up, hybrids, institutions, moral hazard, vertical integration, trucking industry

Determinants of organizational form: Transaction costs and institutions in the European trucking industry

We explain why European trucking carriers are much smaller and rely more heavily on owner-operators (as opposed to employee drivers) than their US counterparts. Our analysis begins by ruling out differences in technology as the source of those disparities and confirms that standard hypotheses in organizational economics, which have been shown to explain the choice of organizational form in US industry, also apply in Europe. We then argue that the preference for subcontracting over vertical integration in Europe is the result of European institutions—particularly, labor regulation and tax laws—that increase the costs of vertical integration.Transaction costs, governance, hybrids, transportation