Online decision making is a kind of machine learning problems where decisions are made in a sequential manner so as to accumulate as many rewards as possible. Typical examples include multi-armed bandit (MAB) problems where an agent needs to decide which arm to pull in each round, and network routing problems where each router needs to decide the next hop for each packet. Thompson sampling (TS) is an efficient and effective algorithm for online decision making problems. Although TS has been proposed for a long time, it was not until recent years that the theoretical guarantees for TS in the standard MAB were given. In this thesis, we first analyze the performance of TS both theoretically and practically in a special MAB called combinatorial MAB with sleeping arms and long-term fairness constraints (CSMAB-F). Then, we apply TS to a novel reactive network routing problem, called \emph{opportunistic routing without link metrics known a priori}, and use the proof techniques we developed for CSMAB-F to analyze the performance. / Graduate

In this dissertation, new theoretical results are obtained for bounding convergence and mean-square error in conditional coding. Further new statistical methods for the practical application of conditional coding are developed. Criteria for the uniform convergence are first examined. Conditional coding Markov chains are aperiodic, π-irreducible, and Harris recurrent. By applying the general theories of uniform ergodicity of Markov chains on genera l state space, one can conclude that conditional coding Markov cha ins are uniformly ergodic and further, theoretical convergence rates based on Doeblin's condition can be found. Conditional coding Markov chains can be also viewed as having finite state space. This allows use of techniques to get bounds on the second largest eigenvalue which lead to bounds on convergence rate and the mean-square error of sample averages. The results are applied in two examples showing that these bounds are useful in practice. Next some algorithms for perfect sampling in conditional coding are studied. An application of exact sampling to the independence sampler is shown to be equivalent to standard rejection sampling. In case of single-site updating, traditional perfect sampling is not directly applicable when the state space has large cardinality and is not stochastically ordered, so a new procedure is developed that gives perfect samples at a predetermined confidence interval. In last chapter procedures and possibilities of applying conditional coding to mixture models are explored. Conditional coding can be used for analysis of a finite mixture model. This methodology is general and easy to use.

Automatic target recognition (ATR) is the ability for a computer to discriminate between different objects in a scene. ATR is often performed on point cloud data from a sensor known as a Ladar. Increasing the resolution of this point cloud in order to get a more clear view of the object in a scene would be of significant interest in an ATR application. A technique to increase the resolution of a scene is known as super resolution. This technique requires many low resolution images that can be combined together. In recent years, however, it has become possible to perform super resolution on a single image. This thesis sought to apply Gabor Wavelets and Compressive Sensing to single image super resolution of digital images of natural scenes. The technique applied to images was then extended to allow the super resolution of a point cloud.

Purpose Wool is still the most valuable and the most versatile fiber used by man. Many questions regarding its production have gone unanswered for centuries. This problem is undertaken in the hope of contributing information which might be used in further study on the problem of wool density. It is recognized that wool density is one of the four major factors affecting the total clean wool production of a sheep. If length of staple, diameter of fiber, and total surface area remain constant, an increase in density brings about a corresponding increase in total production of clean wool. Wool fibers are produced by glands, called fiber follicles, beneath the surface of the skin. Density is controlled by the number of these follicles functioning within a given area. Before great improvement in density can be made, it is necessary to know the mode of inheritance, it is necessary to know the density of each individual involved. Counting the fibere from any sizeable area is not practicable. Therefore, a technique is necessary for sampling the sheep and estimating the density on the basis of sampling figures. Scope The Wira Fleece Caliper is probably the most popular instrument used in sampling for density. To determine the most effective method of using the Wira Caliper, different-sized samples are taken from a given area. Both sides of each sheep are tested, and sheep from different breeds are sampled. Density on all samples is determined by a standard laboratory procedure. The results are statistically analyzed to determine the variation in density as obtained by the different sample sizes. In addition to the main objective, the variation in density between breeds, between sheep of the same brood, and the variation in density between sides on the same sheep is determined.

Les protéines et acides ribonucléiques sont les principaux acteurs de nombreux processus cellulaires.Comprendre leurs fonctions, structures et interactions est un challenge important.Les méthodes expérimentales fournissent des informations sur la structure et la dynamique des molécules.Cependant les méthodes expérimentales sont limitées par le nombre de molécules qu'elles peuvent observer et les moyens qu'elles requièrent.Les méthodes de prédiction permettent d'obtenir des informations structurelles de façon quasi-automatique.Pour s'assurer de leur fiabilité, elles sont testées sur des données expérimentales.Nous présentons une procédure basée sur la cinétique inverse pour trouver une transition entre deux conformations d'un ARN tout en conservant sa structure secondaire.Nous obtenons des résultats comparables à l'état de l'art, ce qui montre que notre sélection des degrés de liberté est pertinente.De plus, nous utilisons des données partielles, ce qui permet d'utiliser différents types de résultats expérimentaux.Nous abordons aussi le problème du repliement protéique par une approche de théorie des jeux.Nous représentons une protéine par un jeu où les joueurs sont les acides aminés et les stratégies, les angles dièdres.La prédiction de structure peut alors être vue comme la recherche d'un équilibre dans un jeu multi-joueur où les fonctions d'utilité correspondent à la qualité du repliement.Nous montrons que l'algorithme de non-regret, appelé Hedge, garantit l'élimination des stratégies dominées et la convergence locale vers un équilibre de Nash.Puis, en limitant notre analyse aux jeux de potentiel, nous montrons qu'une classe plus large d'algorithmes, les algorithmes de régularisation, convergent vers un équilibre de Nash presque surement. / Proteins and Ribonucleic Acids are the workhorses of many cellular processes.Understanding their functions, structures and interactions is an important challenge.Experimental methods provide actual information on structure and dynamics of molecules.However they have limitations : they cannot be applied to all molecules, and they need a lot of resources.Prediction methods are almost automatic ways of obtaining structural information.They are tested on experimental data to attest their reliability.We present, here, approaches tackling different problems.We develop a kinematics-based procedure to morph a RNA molecule between conformations while preserving its secondary structure.We obtain results comparable to state of the art methods showing that our selection of degrees of freedom is efficient.Furthermore we only use sparse information allowing for various kinds of experimental inputs.We also look at the protein structure prediction problem from a game theory angle.We represent the protein dynamics as a game, in which players are amino acids and strategies are dihedrals angles.The structure prediction can thus be seen as finding equilibrium in a multi-players game where all players have utility functions corresponding to the quality of the protein structure.We showed that a well-known no-regret algorithm, called Hedge, guarantees dominated strategies to vanish and a local convergence toward Nash equilibria.Furthermore restricting our analysis to potential games we showed that dual-averaging regularized learning algorithms converge toward a Nash equilibrium almost surely.

Indiana University-Purdue University Indianapolis (IUPUI) / Social dysfunction is a hallmark of schizophrenia and leads to significant disability and distress. Decreased positive and increased negative affect predict poorer social functioning in those with schizophrenia. Social functioning and affect have traditionally been measured in the laboratory; yet, these methods are limited. Experience sampling methods (ESM) offer more immediate, ecologically valid assessments of these constructs. The purpose of this study was to examine social functioning and affect in schizophrenia using a novel form of ESM that passively collects audio data. The two primary hypotheses were: 1) clinical status (schizophrenia versus control) will predict social functioning, level of positive affect, and level of negative affect; and 2) the relationship between clinical status and affect will be moderated by context (social versus non-social). Additional exploratory aims tested the convergent validity between traditional, laboratory-based assessments of social functioning and this novel ESM. Data was collected from 38 people with schizophrenia and 36 control participants; Results partially supported the hypotheses. As expected, laboratory measures of social functioning revealed that those with schizophrenia performed worse than controls. ESM measures of social functioning found that the schizophrenia group interacted with others at the same rate as the control group but did not exhibit as much social engagement. ESM measures of affect revealed the schizophrenia group reported more negative affect than controls, but no differences in positive affect were found. Social context did not moderate the relationship between clinical status and affect. Lastly, correlations between laboratory measures and ESM measures of social functioning were significant for the schizophrenia group but not the control group. Results further our understanding of social functioning and affect in those with schizophrenia and yield important implications for future work.

The questionnaire survey is a key tool for examining social phenomena, but like society as a whole, it is undergoing development and needs to be subjected to constant analysis in order to improve it. The approach of mixed modes of data collection can then be used to evaluate and compare individual modes at the level of measurement invariance in order to point out their degree of measurement accuracy and to evaluate similarity or difference. Through the analysis of political participation, preference and measurement accuracy for three different modes of data collection - CATI, CAWI and CAWI with sampling frame of social network Facebook, clear differences of individual modes were defined and the recommendation of their combination was stated in order to use the strengths they offer, while minimizing the errors associated with them.

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