Bachelor Thesis from the year 2009 in the subject Economics - Other, grade: 5.0, University of Zurich (Sozialökonomisches Institut (SOI)), language: English, abstract: Matching is the part of economics that deals with the question of who gets what, e.g. who gets which jobs, who goes to which university, who receives which organ or who marries whom. During the second part of the last century, many markets have been discovered to have failed in providing the necessary conditions for efficient matches. These market failures have partly evolved on ethical or institutional grounds, but are more generally attributed to congestion or coordination problems caused by the inability of the market to make it safe for participants to act on their private information. For this reason, a variety of allocation mechanisms have been developed and subsequently tested in field and laboratory experiments for possible implementation in real-world applications. This work attempts at giving a condensed review of different matching mechanisms and the performance of algorithms that have been implemented for solving the problems in their respective environments. The theoretical properties of these mechanisms as described in the increasingly vast literature on matching design will be used as a benchmark to compare their relative performance in terms of overall efficiency. The results yield some basic insights in the varying success of the competing algorithms in practice, indicating that both the quality of theoretical predictions and the actual performance of the algorithms decrease with the complexity of market environments. In particular, they show that imperfections of markets such as information asymmetry and incentive problems can have far-reaching consequences with respect to the effective working of matching procedures.

Bachelor Thesis from the year 2009 in the subject Economics - Other, grade: 5.0, University of Zurich (Sozialökonomisches Institut (SOI)), language: English, abstract: Matching is the part of economics that deals with the question of who gets what, e.g. who gets which jobs, who goes to which university, who receives which organ or who marries whom. During the second part of the last century, many markets have been discovered to have failed in providing the necessary conditions for efficient matches. These market failures have partly evolved on ethical or institutional grounds, but are more generally attributed to congestion or coordination problems caused by the inability of the market to make it safe for participants to act on their private information. For this reason, a variety of allocation mechanisms have been developed and subsequently tested in field and laboratory experiments for possible implementation in real-world applications. This work attempts at giving a condensed review of different matching mechanisms and the performance of algorithms that have been implemented for solving the problems in their respective environments. The theoretical properties of these mechanisms as described in the increasingly vast literature on matching design will be used as a benchmark to compare their relative performance in terms of overall efficiency. The results yield some basic insights in the varying success of the competing algorithms in practice, indicating that both the quality of theoretical predictions and the actual performance of the algorithms decrease with the complexity of market environments. In particular, they show that imperfections of markets such as information asymmetry and incentive problems can have far-reaching consequences with respect to the effective working of matching procedures.

Two-sided matching provides a model of search processes such as those between firms and workers in labor markets or between buyers and sellers in auctions. This book gives a comprehensive account of recent results concerning the game-theoretic analysis of two-sided matching. The focus of the book is on the stability of outcomes, on the incentives that different rules of organization give to agents, and on the constraints that these incentives impose on the ways such markets can be organized. The results for this wide range of related models and matching situations help clarify which conclusions depend on particular modeling assumptions and market conditions, and which are robust over a wide range of conditions. 'This book chronicles one of the outstanding success stories of the theory of games, a story in which the authors have played a major role: the theory and practice of matching markets ... The authors are to be warmly congratulated for this fine piece of work, which is quite unique in the game-theoretic literature.' From the Foreword by Robert Aumann

The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

While most college admission markets are decentralized, the United Kingdom, home to one of the most prestigious markets for higher education, operates a centralized system. The thesis at hand analyses the efficiency of the match this system generates and its main determinants. The efficiency is found to be surprisingly high given the fact that the system for matching student and colleges deviates greatly from what has been identified to be optimal in theory. While the matching mechanism does in theory exhibit substantial flaws, these do not substantially affect the outcome in practice as students and colleges act highly rational and hereby ensure the functioning of the market.

This book constitutes the refereed proceedings of the 44th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2018, held in Krems, Austria, in January/February 2018. The 48 papers presented in this volume were carefully reviewed and selected from 97 submissions. They were organized in topical sections named: foundations of computer science; software engineering: advances methods, applications, and tools; data, information and knowledge engineering; network science and parameterized complexity; model-based software engineering; computational models and complexity; software quality assurance and transformation; graph structure and computation; business processes, protocols, and mobile networks; mobile robots and server systems; automata, complexity, completeness; recognition and generation; optimization, probabilistic analysis, and sorting; filters, configurations, and picture encoding; machine learning; text searching algorithms; and data model engineering.

There is more statistical data produced in today’s modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching allows just that; it is the art of combining information from different sources (particularly sample surveys) that contain no common unit. In response to modern influxes of data, it is an area of rapidly growing interest and complexity. Statistical Matching: Theory and Practice introduces the basics of statistical matching, before going on to offer a detailed, up-to-date overview of the methods used and an examination of their practical applications. Presents a unified framework for both theoretical and practical aspects of statistical matching. Provides a detailed description covering all the steps needed to perform statistical matching. Contains a critical overview of the available statistical matching methods. Discusses all the major issues in detail, such as the Conditional Independence Assumption and the assessment of uncertainty. Includes numerous examples and applications, enabling the reader to apply the methods in their own work. Features an appendix detailing algorithms written in the R language. Statistical Matching: Theory and Practice presents a comprehensive exploration of an increasingly important area. Ideal for researchers in national statistics institutes and applied statisticians, it will also prove to be an invaluable text for scientists and researchers from all disciplines engaged in the multivariate analysis of data collected from different sources.