Unsupervised Domain Adaptation with Copula Models

We study the task of unsupervised domain adaptation, where no labeled data from the target domain is provided during training time. To deal with the potential discrepancy between the source and target distributions, both in features and labels, we exploit a copula-based regression framework. The benefits of this approach are two-fold: (a) it allows us to model a broader range of conditional predictive densities beyond the common exponential family, (b) we show how to leverage Sklar's theorem, the essence of the copula formulation relating the joint density to the copula dependency functions, to find effective feature mappings that mitigate the domain mismatch. By transforming the data to a copula domain, we show on a number of benchmark datasets (including human emotion estimation), and using different regression models for prediction, that we can achieve a more robust and accurate estimation of target labels, compared to recently proposed feature transformation (adaptation) methods.Comment: IEEE International Workshop On Machine Learning for Signal Processing 201

QUASII: QUery-Aware Spatial Incremental Index.

With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected. Traditional systems require indexes to be built before analytic queries can be executed efficiently. Such an indexing step requires substantial computing resources and introduces a considerable and growing data-to-insight gap where scientists need to wait before they can perform any analysis. Moreover, scientists often only use a small fraction of the data - the parts containing interesting phenomena - and indexing it fully does not always pay off. In this paper we develop a novel incremental index for the exploration of spatial data. Our approach, QUASII, builds a data-oriented index as a side-effect of query execution. QUASII distributes the cost of indexing across all queries, while building the index structure only for the subset of data queried. It reduces data-to-insight time and curbs the cost of incremental indexing by gradually and partially sorting the data, while producing a data-oriented hierarchical structure at the same time. As our experiments show, QUASII reduces the data-to-insight time by up to a factor of 11.4x, while its performance converges to that of the state-of-the-art static indexes

Geometry of abstraction in quantum computation

Quantum algorithms are sequences of abstract operations, per­ formed on non-existent computers. They are in obvious need of categorical semantics. We present some steps in this direction, following earlier contribu­ tions of Abramsky, Goecke and Selinger. In particular, we analyze function abstraction in quantum computation, which turns out to characterize its clas­ sical interfaces. Intuitively, classical data can be recognized as just those data that can be manipulated using variables, i.e. copied, deleted, and abstracted over. A categorical framework of polynomial extensions provides a convenient language for specifying quantum algorithms, with a clearly distinguished clas­ sical fragment, familiar from functional \ud programming. As a running example, we reconstruct Simon's algorithm, which is a sim­ ple predecessor of Shor's quantum algorithms for factoring and discrete loga­ rithms. The abstract specification in the framework of polynomial categories displays some of the fundamental program transformations involved in devel­ oping quantum algorithms, and points to the computational resources, whether quantum or classical, which are necessary for the various parts of the execution. The relevant resources are characterized as categorical structures. They are normally supported by the standard Hilbert space model of quantum mechan­ ics, but in some cases they can also be found in other, nonstandard models. We conclude the paper by sketching an implementation of Simon's algorithm using just abelian groups and relations.\u

Proposal for a Mesoscopic Optical Berry-Phase Interferometer

We propose a novel spin-optronic device based on the interference of polaritonic waves traveling in opposite directions and gaining topological Berry phase. It is governed by the ratio of the TE-TM and Zeeman splittings, which can be used to control the output intensity. Because of the peculiar orientation of the TE-TM effective magnetic field for polaritons, there is no analogue of the Aharonov- Casher phase shift existing for electrons.Comment: 4 page

Correlating matched-filter model for analysis and optimisation of neural networks

A new formalism is described for modelling neural networks by means of which a clear physical understanding of the network behaviour can be gained. In essence, the neural net is represented by an equivalent network of matched filters which is then analysed by standard correlation techniques. The procedure is demonstrated on the synchronous Little-Hopfield network. It is shown how the ability of this network to discriminate between stored binary, bipolar codes is optimised if the stored codes are chosen to be orthogonal. However, such a choice will not often be possible and so a new neural network architecture is proposed which enables the same discrimination to be obtained for arbitrary stored codes. The most efficient convergence of the synchronous Little-Hopfield net is obtained when the neurons are connected to themselves with a weight equal to the number of stored codes. The processing gain is presented for this case. The paper goes on to show how this modelling technique can be extended to analyse the behaviour of both hard and soft neural threshold responses and a novel time-dependent threshold response is described

Evaluation of magnetic materials for static inverters and converters

Program studies materials for use in static inverters and converters. It gives suitable data on the behavior of commonly used materials when excited with square wave power

High School Class for Gifted Pupils in Physics and Sciences and Pupils` Skills Measured by Standard and Pisa Test

The ``High school class for students with special abilities in physics`` was founded in Nis, Serbia in 2003. The basic aim of this project has been introducing a broadened curriculum of physics, mathematics, computer science, as well as chemistry and biology. We present analysis of the pupils` skills in solving rather problem oriented test, as PISA test, and compare their results with the results of pupils who study under standard curricula. Analysis of achievement data should clarify what are benefits of introducing in school system track for gifted students. Additionally, item analysis helps in understanding and improvement of learning strategies efficacy.Comment: 6 pages, Talk given at 7th International Conference of the Balkan Physical Union, Alexandruoplos, Greece, 9-13 September 2009. To be published in AIP Conf.Pro

Highly efficient fe simulations by means of simplified corotational formulation

Finite Element Method (FEM) has deservedly gained the reputation of the most powerful numerical method in the field of structural analysis. It offers tools to perform various kinds of simulations in this field, ranging from static linear to nonlinear dynamic analyses. In recent years, a particular challenge is development of FE formulations that enable highly efficient simulations, aiming at real-time dynamic simulations as a final objective while keeping high simulation fidelity such as nonlinear effects. The authors of this paper propose a simplified corotational FE formulation as a possible solution to this challenge. The basic idea is to keep the linear behavior of each element in the FE assemblage, but to extract the rigid-body motion on the element level and include it in the formulation to cover geometric nonlinearities. This paper elaborates the idea and demonstrates it on static cases with three different finite element types. The objective is to check the achievable accuracy based on such a simplified geometrically nonlinear FE formulation. In the considered examples, the difference between the results obtained with the present formulation and those by rigorous formulations is less than 3% although fairly large deformations are induced