Statistical Learning for Structured Models: Tree Based Methods and Neural Networks

In this thesis, estimation in regression and classification problems which include low dimensional structures are considered. The underlying question is the following. How well do statistical learn- ing methods perform for models with low dimensional structures? We approach this question using various algorithms in various settings. For our first main contribution, we prove optimal convergence rates in a classification setting using neural networks. While non-optimal rates ex- isted for this problem, we are the first to prove optimal ones. Secondly, we introduce a new tree based algorithm we named random planted forest. It adapts particularly well to models which consist of low dimensional structures. We examine its performance in simulation studies and include some theoretical backing by proving optimal convergence rates in certain settings for a modification of the algorithm. Additionally, a generalized version of the algorithm is included, which can be used in classification settings. In a further contribution, we prove optimal con- vergence rates for the local linear smooth backfitting algorithm. While such rates have already been established, we bring a new simpler perspective to the problem which leads to better understanding and easier interpretation. Additionally, given an estimator in a regression setting, we propose a constraint which leads to a unique decomposition. This decomposition is useful for visualising and interpreting the estimator, in particular if it consits of low dimenional structures

Bid-Centric Cloud Service Provisioning

Bid-centric service descriptions have the potential to offer a new cloud service provisioning model that promotes portability, diversity of choice and differentiation between providers. A bid matching model based on requirements and capabilities is presented that provides the basis for such an approach. In order to facilitate the bidding process, tenders should be specified as abstractly as possible so that the solution space is not needlessly restricted. To this end, we describe how partial TOSCA service descriptions allow for a range of diverse solutions to be proposed by multiple providers in response to tenders. Rather than adopting a lowest common denominator approach, true portability should allow for the relative strengths and differentiating features of cloud service providers to be applied to bids. With this in mind, we describe how TOSCA service descriptions could be augmented with additional information in order to facilitate heterogeneity in proposed solutions, such as the use of coprocessors and provider-specific services

The visual dimension in organizing, organization, and organization research: Core ideas, current developments, and promising avenues

With the unprecedented rise in the use of visuals, and its undeniable omnipresence in organizational contexts, as well as in the individual's everyday life, organization and management science has recently started to pay closer attention to the to date under-theorized "visual mode" of discourse and meaning construction. Building primarily on insights from the phenomenological tradition in organization theory and from social semiotics, this article sets out to consolidate previous scholarly efforts and to sketch a fertile future research agenda. After briefly exploring the workings of visuals, we introduce the methodological and theoretical "roots" of visual studies in a number of disciplines that have a long-standing tradition of incorporating the visual. We then continue by extensively reviewing work in the field of organization and management studies: More specifically, we present five distinct approaches to feature visuals in research designs and to include the visual dimension in scholarly inquiry. Subsequently, we outline, in some detail, promising avenues for future research, and close with a reflection on the impact of visualization on scientific practice itself. (authors' abstract

Fluid-crystal coexistence for proteins and inorganic nanocolloids: dependence on ionic strength

We investigate theoretically the fluid-crystal coexistence of solutions of globular charged nanoparticles like proteins and inorganic colloids. The thermodynamic properties of the fluid phase are computed via the optimized Baxter model. This is done specifically for lysozyme and silicotungstates for which the bare adhesion parameters are evaluated via the experimental second virial coefficients. The electrostatic free energy of the crystal is approximated by supposing the cavities in the interstitial phase between the particles are spherical in form. In the salt-free case a Poisson-Boltzmann equation is solved to calculate the effective charge on a particle and a Donnan approximation is used to derive the chemical potential and osmotic pressure in the presence of salt. The coexistence data of lysozyme and silicotungstates are analyzed within this scheme, especially with regard to the ionic-strength dependence of the chemical potentials. The latter agree within the two phases provided some upward adjustment of the effective charge is allowed for.Comment: 15 pages, 9 figure

Suppression of spin-exchange relaxation in tilted magnetic fields within the geophysical range

We present a detailed experimental and theoretical study on the relaxation of spin coherence due to the spin-exchange mechanism arising in the electronic ground states of alkali-metal vapor atoms. As opposed to the well-explored formation of a stretched state in a longitudinal geometry (magnetic field parallel to the laser propagation direction) we employ adapted hyperfine-selective optical pumping in order to suppress spin-exchange relaxation. By comparing measurements of the intrinsic relaxation rate of the spin coherence in the ground state of cesium atoms with detailed density-matrix simulations we show that the relaxation due to spin-exchange collisions can be reduced substantially even in a tilted magnetic field of geomagnetic strength, the major application case of scalar magnetic surveying. This explains the observed striking improvement in sensitivity and further deepens the understanding of the light- narrowed Mx magnetometer, which was presented recently. Additionally, new avenues for investigating the dynamics in alkali-metal atoms governed by the spin-exchange interaction and interacting with arbitrary external fields open up

Adiabatic processes need not correspond to optimal work

The minimum work principle states that work done on a thermally isolated equilibrium system is minimal for the adiabatically slow (reversible) realization of a given process. This principle, one of the formulations of the second law, is studied here for finite (possibly large) quantum systems interacting with macroscopic sources of work. It is shown to be valid as long as the adiabatic energy levels do not cross. If level crossing does occur, counter examples are discussed, showing that the minimum work principle can be violated and that optimal processes are neither adiabatically slow nor reversible.Comment: 5 pages, 1 figure, revtex

Processing and transaction concepts for cooperation of engineering workstations and a database server

A DBMS kernel architecture is proposed for improved DB support of engineering applications running on a cluster of workstations. Using such an approach, part of the DBMS code - an application-specific layer - is allocated close to the corresponding application on a workstation while the kernel code is executed on a central server. Emperical performance results from DB-based engineering applications are reported to justify the chosen DBMS architecture. The paper focuses on design issues of the application layer including server coupling, processing model and application interface. Moreover, a transaction model for long-term database work in a coupled workstation-server environment is investigated in detail

PRIMA : a DBMS prototype supporting engineering applications

The design of the Molecule-Atom Data model, aimed at the effective support of engineering applications, is justified and described with its essential properties and features. MAD offers direct and symmetric management of network structures and recursiveness, dynamic object definition and object handling allowing for both vertical and horizontal access. Its prototype implementation PRIMA is discussed using a multi-level model for the DBMS architecture. Our DBMS kernel provides a variety of access path structures, tuning mechanisms, and performance enhancements transparent at the data model interface. PRIMA is assumed to be used in different run-time environments including workstation coupling and multi-processor systems. In particular, it serves as a research vehicle to investigate the exploitation of "semantic parallelism" in single user operations

Coupling engineering workstations to a database server

A DBMS kernel architecture is proposed for improved DB support of engineering applications running on a cluster 01 workstations. Using such an approach, part of the DBMS code - an application-specific layer - is allocated close to the corresponding application on a workstation while the kernel code is executed on a central server. Empirical performance results from DB-based engineering applications are reported to justify the chosen DBMS architecture. The paper focuses on design issues of the application layer including server coupling, processing model and application interface. Moreover, a transaction model for long-term database work in a coupled workstation-server environment is investigated in detail