Filtern
Erscheinungsjahr
- 2011 (24) (entfernen)
Dokumenttyp
- Dissertation (19)
- Buch (Monographie) (3)
- Konferenzveröffentlichung (1)
- Masterarbeit (1)
Sprache
- Englisch (24) (entfernen)
Schlagworte
- Hydrocortison (4)
- Stress (4)
- Neuroendokrines System (3)
- behavioral genetics (2)
- stress (2)
- Algorithmische Lerntheorie (1)
- Alterität (1)
- Arbeitslosenversicherung (1)
- Asia (1)
- Asien (1)
- Automata Theory (1)
- Automatentheorie (1)
- Außenpolitik (1)
- Black Rapist (1)
- Borderline Personality Disorder (1)
- Borderline-Persönlichkeitsstörung (1)
- Brain (1)
- Bregman distance (1)
- Bregman-Distanz (1)
- Business data (1)
- Bündel-Methode (1)
- Bürgerrechtsbewegung (1)
- CASL (1)
- CBG (1)
- Consumer confidence (1)
- Consumer need for uniqueness (1)
- Corticosteroid-bindendes Globulin (1)
- Degradation (1)
- Depression (1)
- Deutschland (1)
- Directed Graphs (1)
- Distractor-Response Binding (1)
- Distraktor-Verarbeitung (1)
- Education (1)
- Elektroencephalographie (1)
- Entscheidung bei Unsicherheit (1)
- Enzyme (1)
- Epigenetik (1)
- Europa (1)
- Europe (1)
- European Union (1)
- Europäische Union (1)
- Event-File (1)
- Fahrassistenzsystem (1)
- Fernerkundung (1)
- Fetus (1)
- Formal languages (1)
- Funktionelle NMR-Tomographie (1)
- GR (1)
- Gedächtnis (1)
- Gerichteter Graph (1)
- German criminal law (1)
- Germany (1)
- Geschlecht (1)
- Globale Konvergenz (1)
- Glucocorticosteroide (1)
- Glukokortikoidrezeptor (1)
- Graph Minors (1)
- Graph Rewriting (1)
- HPA (1)
- Habituation (1)
- Handlungsregulation (1)
- Hirnforschung (1)
- Hong Kong (1)
- Hongkong (1)
- Identität (1)
- Implizites Lernen (1)
- Implizites Sequenzlernen (1)
- Infusion (1)
- Innere-Punkte-Methode (1)
- Insulin (1)
- Invisible Man (1)
- Islamic Banking (1)
- Islamic Finance (1)
- Islamische Bank (1)
- Islamisches Finanzwesen (1)
- Japan (1)
- Kastration (1)
- Klassische Konditionierung (1)
- Kleinman (1)
- Kognition (1)
- Konsumentenvertrauen (1)
- Konvexe Optimierung (1)
- Kortex (1)
- Körper (1)
- Landdegradation (1)
- Lebensqualität (1)
- Lynching (1)
- MR (1)
- Maskulinität (1)
- Mass Customization (1)
- Mathematische Lerntheorie (1)
- Mediterranean (1)
- Memory (1)
- Mineralokortikoidrezeptor (1)
- Minor <Graphentheorie> (1)
- Mittelmeerraum (1)
- Monitoring (1)
- Monte-Carlo-Simulation (1)
- Männlichkeit (1)
- NOAA AVHRR (1)
- Newton (1)
- Newton-Verfahren (1)
- Nichtglatte Optimierung (1)
- Opting out of School Obligations for Religious Reasons (1)
- P-Glykoprotein (1)
- Perfusion (1)
- Persönlichkeitsstörung (1)
- Plazenta (1)
- Polymorphismus (1)
- Precautionary saving (1)
- Proximal-Punkt-Verfahren (1)
- Psychiatric genetics (1)
- Psychische Störung (1)
- Raketenabwehr (1)
- Ralph Ellison (1)
- Rasse (1)
- Rassenmischung (1)
- Reduktionssystem (1)
- Regular Expressions (1)
- Regularisierungsverfahren (1)
- Regulärer Ausdruck (1)
- Reiz-Reaktions Bindung (1)
- Religion (1)
- Religionsausübung (1)
- Religionsunterricht (1)
- Religious Instruction (1)
- Religiöse Identität (1)
- Robust methods (1)
- Robuste Schätzung (1)
- Rollentheorie (1)
- Räumliche Statistik (1)
- Rückmeldung (1)
- Saving behaviour (1)
- Scharia (1)
- Schreckreflex (1)
- Schulbuchstreit (1)
- Schwangersch (1)
- Schwangerschaft (1)
- Sekundärkrankheit (1)
- Selbst-Concordanz (1)
- Sexualität (1)
- Sharia (1)
- Sicherheitspolitik (1)
- Simulation study (1)
- Small Area Estimation (1)
- Small Area Verfahren (1)
- Sparverhalten (1)
- Spatial correlation (1)
- Steroidhormonrezeptor (1)
- Stillen (1)
- Strafbarkeit (1)
- Strafjustiz (1)
- Strafrecht (1)
- Stressreaktion (1)
- Subarachnoidalblutung (1)
- Subjective income uncertainty (1)
- Terrestrisches ükosystem (1)
- Thalamus (1)
- Theoretische Informatik (1)
- Transkript (1)
- Trockengebiet (1)
- Uncle Tom (1)
- Unemployment benefits (1)
- Unternehmensdaten (1)
- Unterrichtsbefreiung (1)
- Variationsungleichung (1)
- Verbraucherverhalten (1)
- Vergangenheitsbewältigung (1)
- Vergewaltigung (1)
- Verhaltensgenetik (1)
- Vorsichtssparen (1)
- Zeitreihe (1)
- action control (1)
- alternative Transkriptionsvarianten (1)
- alternative transcription variant (1)
- auxiliary problem principle (1)
- bundle-method (1)
- convergence (1)
- cortex (1)
- cortisol (1)
- criminal liability (1)
- customer loyalty (1)
- driver assistance system (1)
- drylands (1)
- epigenetic programming (1)
- executive functions (1)
- exekutive Funktionen (1)
- foreign policy (1)
- gender (1)
- glucocorticoid receptor (1)
- glucocorticoids (1)
- grammatical inference (1)
- history textbook dispute (1)
- hypothalamo-pituitary-adrenal-axis (1)
- hypothalamus-pituitary-adrenal axis (1)
- implicit learning (1)
- inexact (1)
- land degradattion (1)
- logarithmic-quadratic distance function (1)
- logarithmisch-quadratische Distanzfunktion (1)
- mineralocorticoid receptor (1)
- miscegenation (1)
- missile defense (1)
- monotone (1)
- neuroendocrine system (1)
- nicht-genomische Effekte (1)
- non-genomic effects (1)
- overloading of criminal justice (1)
- p-glycoprotein (1)
- placenta (1)
- prenatal adversity (1)
- prenatal programming (1)
- prenatal stress (1)
- prenatal tobacco exposure (1)
- pränatale Programmierung (1)
- pränatale Risikofaktoren (1)
- pränatale Tabakexposition (1)
- pränataler Stress (1)
- race (1)
- rape (1)
- role theory (1)
- secondary party (1)
- security policy (1)
- self-concodrance (1)
- somatische Komorbiditäten (1)
- stress hyporesponsive period (1)
- stress reaction (1)
- subarachnoid haemorrhage (1)
- subjektive Einkommensunsicherheit (1)
- time series analysis (1)
- uniqueness seeking (1)
- Ätiologie (1)
- Öffentliche Schule (1)
- Überlastung (1)
- ükosystem (1)
Institut
- Psychologie (11)
- Rechtswissenschaft (4)
- Informatik (2)
- Mathematik (2)
- Wirtschaftswissenschaften (2)
- Anglistik (1)
- Politikwissenschaft (1)
- Raum- und Umweltwissenschaften (1)
This thesis centers on formal tree languages and on their learnability by algorithmic methods in abstractions of several learning settings. After a general introduction, we present a survey of relevant definitions for the formal tree concept as well as special cases (strings) and refinements (multi-dimensional trees) thereof. In Chapter 3 we discuss the theoretical foundations of algorithmic learning in a specific type of setting of particular interest in the area of Grammatical Inference where the task consists in deriving a correct formal description for an unknown target language from various information sources (queries and/or finite samples) in a polynomial number of steps. We develop a parameterized meta-algorithm that incorporates several prominent learning algorithms from the literature in order to highlight the basic routines which regardless of the nature of the information sources have to be run through by all those algorithms alike. In this framework, the intended target descriptions are deterministic finite-state tree automata. We discuss the limited transferability of this approach to another class of descriptions, residual finite-state tree automata, for which we propose several learning algorithms as well. The learnable class by these techniques corresponds to the class of regular tree languages. In Chapter 4we outline a recent range of attempts in Grammatical Inference to extend the learnable language classes beyond regularity and even beyond context-freeness by techniques based on syntactic observations which can be subsumed under the term 'distributional learning', and we describe learning algorithms in several settings for the tree case taking this approach. We conclude with some general reflections on the notion of learning from structural information.
Variational inequality problems constitute a common basis to investigate the theory and algorithms for many problems in mathematical physics, in economy as well as in natural and technical sciences. They appear in a variety of mathematical applications like convex programming, game theory and economic equilibrium problems, but also in fluid mechanics, physics of solid bodies and others. Many variational inequalities arising from applications are ill-posed. This means, for example, that the solution is not unique, or that small deviations in the data can cause large deviations in the solution. In such a situation, standard solution methods converge very slowly or even fail. In this case, so-called regularization methods are the methods of choice. They have the advantage that an ill-posed original problem is replaced by a sequence of well-posed auxiliary problems, which have better properties (like, e.g., a unique solution and a better conditionality). Moreover, a suitable choice of the regularization term can lead to unconstrained auxiliary problems that are even equivalent to optimization problems. The development and improvement of such methods are a focus of current research, in which we take part with this thesis. We suggest and investigate a logarithmic-quadratic proximal auxiliary problem (LQPAP) method that combines the advantages of the well-known proximal-point algorithm and the so-called auxiliary problem principle. Its exploration and convergence analysis is one of the main results in this work. The LQPAP method continues the recent developments of regularization methods. It includes different techniques presented in literature to improve the numerical stability: The logarithmic-quadratic distance function constitutes an interior point effect which allows to treat the auxiliary problems as unconstrained ones. Furthermore, outer operator approximations are considered. This simplifies the numerical solution of variational inequalities with multi-valued operators since, for example, bundle-techniques can be applied. With respect to the numerical practicability, inexact solutions of the auxiliary problems are allowed using a summable-error criterion that is easy to implement. As a further advantage of the logarithmic-quadratic distance we verify that it is self-concordant (in the sense of Nesterov/Nemirovskii). This motivates to apply the Newton method for the solution of the auxiliary problems. In the numerical part of the thesis the LQPAP method is applied to linearly constrained, differentiable and nondifferentiable convex optimization problems, as well as to nonsymmetric variational inequalities with co-coercive operators. It can often be observed that the sequence of iterates reaches the boundary of the feasible set before being close to an optimal solution. Against this background, we present the strategy of under-relaxation, which robustifies the LQPAP method. Furthermore, we compare the results with an appropriate method based on Bregman distances (BrPAP method). For differentiable, convex optimization problems we describe the implementation of the Newton method to solve the auxiliary problems and carry out different numerical experiments. For example, an adaptive choice of the initial regularization parameter and a combination of an Armijo and a self-concordance step size are evaluated. Test examples for nonsymmetric variational inequalities are hardly available in literature. Therefore, we present a geometric and an analytic approach to generate test examples with known solution(s). To solve the auxiliary problems in the case of nondifferentiable, convex optimization problems we apply the well-known bundle technique. The implementation is described in detail and the involved functions and sequences of parameters are discussed. As far as possible, our analysis is substantiated by new theoretical results. Furthermore, it is explained in detail how the bundle auxiliary problems are solved with a primal-dual interior point method. Such investigations have by now only been published for Bregman distances. The LQPAP bundle method is again applied to several test examples from literature. Thus, this thesis builds a bridge between theoretical and numerical investigations of solution methods for variational inequalities.
Extension of inexact Kleinman-Newton methods to a general monotonicity preserving convergence theory
(2011)
The thesis at hand considers inexact Newton methods in combination with algebraic Riccati equation. A monotone convergence behaviour is proven, which enables a non-local convergence. Above relation is transferred to a general convergence theory for inexact Newton methods securing the monotonicity of the iterates for convex or concave mappings. Several application prove the pratical benefits of the new developed theory.
The overall objective of this thesis was to gain a deeper understanding of the antecedents, processes, and manifestations of uniqueness-driven consumer behavior. To achieve this goal, five studies have been conducted in Germany and Switzerland with a total of 1048 participants across different demographic and socio-economic backgrounds. Two concepts were employed in all studies: Consumer need for uniqueness (CNFU) and general uniqueness perception (GUP). CNFU (Tian, Bearden, & Hunter, 2001), a mainly US"based consumer research concept, measures the individual need, and thus the motivation to acquire, use, and dispose consumer goods in order to develop a unique image. GUP, adapted from the two-component theory of individuality (Kampmeier, 2001), represents a global and direct measure of self-ascribed uniqueness. Study #1 looked at the interrelation of the uniqueness-driven concepts. Therefore, GUP and CNFU were employed in the study as potential psychological factors that influence and predict uniqueness-driven consumer behavior. Different behavioral measures were used: The newly developed possession of individualized products (POIP), the newly developed products for uniqueness display (PFUD), and the already established uniqueness-enhancing behaviors (UEB). Analyses showed that CNFU mediates the relationship between GUP and the behavioral measures in a German speaking setting. Thus, GUP (representing self-perception) was identified as the driver behind CNFU (representing motivation) and the actual consumer behavior. Study #2 examined further manifestations of uniqueness-driven consumer behavior. For this purpose, an extreme form of uniqueness-increasing behavior was researched: Tattooing. The influence of GUP and CNFU on tattooing behavior was investigated using a sample derived from a tattoo exhibition. To do so, a newly developed measure to determine the percentage of the body covered by tattoos was employed. It was revealed that individuals with higher GUP and CNFU levels indeed have a higher tattooing degree. Study #3 further explored the predictive possibilities and limitations of the GUP and CNFU concepts. On the one hand, study #3 specifically looked at the consumption of customized apparel products as mass customization is said to become the standard of the century (Piller & Müller, 2004). It was shown that individuals with higher CNFU levels not only purchased more customized apparel products in the last six months, but also spend more money on them. On the other hand, uniqueness-enhancing activities (UEA), such as travel to exotic places or extreme sports, were investigated by using a newly developed 30-item scale. It was revealed that CNFU partly mediates the GUP and UEA relationship, proving that CNFU indeed predicts a broad range of consumer behaviors and that GUP is the driver behind the need and the behavior. Study #4, entered a new terrain. In contrast to the previous three studies, it explored the so termed "passive" side of uniqueness-seeking in the consumer context. Individuals might feel unique because business companies treat them in a special way. Such a unique customer treatment (UCT) involves activities like customer service or customer relationship management. Study #4 investigated if individuals differ in their need for such a treatment. Hence, with the need for unique customer treatment (NFUCT) a new uniqueness-driven consumer need was introduced and its impact on customer loyalty examined. Analyses, for example, revealed that individuals with high NFUCT levels receiving a high unique customer treatment (UCT) showed the highest customer loyalty, whereas the lowest customer loyalty was found among those individuals with high NFUCT levels receiving a low unique customer treatment (UCT). Study #5 mainly examined the processes behind uniqueness-driven consumer behavior. Here, not only the psychological influences, but also situational influences were examined. This study investigated the impact of a non-personal "indirect" uniqueness manipulation on the consumption of customized apparel products by simultaneously controlling for the influence of GUP and CNFU. Therefore, two equal experimental groups were created. Afterwards, these groups either received an e-mail with a "pro-individualism" campaign or a "pro-collectivism" campaign especially developed for study #5. The conducted experiment revealed that, individuals receiving a "pro-individualism" poster campaign telling the participants that uniqueness is socially appropriate and desired were willing to spend more money on customization options compared to individuals receiving a "pro-collectivism" poster campaign. Hence, not only psychological antecedents such as GUP and CNFU influence uniqueness-driven consumer behavior, but also situational factors.