الصفحة 22
الصفحة 22
Innovations in Quantitative Risk Management ; TU München, September 2013
The KPMG Center of Excellence in Risk Management conference Risk Management Reloaded and this proceedings volume contribute to bridging the gap between academia –providing methodological advances– and practice –having a firm understanding of the economic conditions in which a given model is used. Discussed fields of application range from asset management, credit risk, and energy to risk management issues in insurance. Methodologically, dependence modeling, multiple-curve interest rate-models, and model risk are addressed. Finally, regulatory developments and possible limits of mathematical modeling are discussed.
Innovations in Derivatives Markets : Fixed Income Modeling, Valuation Adjustments, Risk Management, and Regulation
This book presents 20 peer-reviewed chapters on current aspects of derivatives markets and derivative pricing. The contributions, written by leading researchers in the field as well as experienced authors from the financial industry, present the state of the art in: • Modeling counterparty credit risk: credit valuation adjustment, debit valuation adjustment, funding valuation adjustment, and wrong way risk. • Pricing and hedging in fixed-income markets and multi-curve interest-rate modeling. • Recent developments concerning contingent convertible bonds, the measuring of basis spreads, and the modeling of implied correlations.
Innovations in classification, data science, and information systems ; Proceedings of the 27th Annual Conference of the Gesellschaft für Klassifikation e.V., Brandenburg University of Technology, Cottbus, March 12-14, 2003
The volume presents innovations in data analysis and classification and gives an overview of the state of the art in these scientific fields and applications. Areas that receive considerable attention in the book are discrimination and clustering, data analysis and statistics, as well as applications in marketing, finance, and medicine. The reader will find material on recent technical and methodological developments and a large number of applications demonstrating the usefulness of the newly developed techniques.
Innovations in Bayesian Networks : Theory and Applications
Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field.
Innovations for requirement analysis : From stakeholders needs to formal designs ; 14th Monterey Workshop 2007, Monterey, CA, USA, September 10-13, 2007. Revised Selected Papers
This book presents the thoroughly refereed and revised proceedings of the 14th Monterey workshop, held in Monterey, CA, USA, September 10-13, 2007. The theme of the workshop was Innovations for Requirement Analysis: From Stakeholders' Needs to Formal Designs.The 10 revised full papers included in the book were carefully selected during two rounds of reviewing and revision. These are preceded by the abstracts of the three keynote talks as well as a detailed introduction to the theme of the workshop, including a case study used by many participants to frame their analyses, and a summary of the workshop's results.
Information Technologies in Biomedicine
As the medical information systems have been integrated in order to address the core of medicine, including patient care in ambulatory and in-patient setting, computer assisted diagnosis and treatment, telemedicine, and home care we are witnessing radical changes in the Information Technologies. This will continue in the years to come. This book presents a comprehensive study in this field and contains carefully selected articles contributed by experts of information technologies.
Information security and privacy ; 25th Australasian Conference, ACISP 2020, Perth, WA, Australia, November 30 – December 2, 2020, Proceedings
This book constitutes the refereed proceedings of the 25th Australasian Conference on Information Security and Privacy, ACISP 2020, held in Perth, WA, Australia, in November 2020*. The 31 revised full papers and 5 short papers presented were carefully revised and selected from 151 submissions. The papers present and discuss the latest research, trends, breakthroughs, and challenges in the domain of information security, privacy and cybersecurity on a variety of topics such as post-quantum cryptography; symmetric cipher; signature; network security and blockchain; cryptographic primitives; mathematical foundation; machine learning security, among others.
Information Processing with Evolutionary Algorithms : From Industrial Applications to Academic Speculations
The last decade of the 20th century has witnessed a surge of interest in num- ical, computation-intensive approaches to information processing. The lines that draw the boundaries among statistics, optimization, arti cial intelligence and information processing are disappearing, and it is not uncommon to nd well-founded and sophisticated mathematical approaches in application - mains traditionally associated with ad-hoc programming. Heuristics has - come a branch of optimization and statistics. Clustering is applied to analyze soft data and to provide fast indexing in the World Wide Web. Non-trivial matrix algebra is at the heart of the last advances in computer vision. The breakthrough impulse was, apparently, due to the rise of the interest in arti cial neural networks, after its rediscovery in the late 1980s. Disguised as ANN, numerical and statistical methods made an appearance in the - formation processing scene, and others followed. A key component in many intelligent computational processing is the search for an optimal value of some function. Sometimes, this function is not evident and it must be made explicit in order to formulate the problem as an optimization problem. The search - ten takes place in high-dimensional spaces that can be either discrete, or c- tinuous or mixed. The shape of the high-dimensional surface that corresponds to the optimized function is usually very complex. Evolutionary algorithms are increasingly being applied to information processing applications that require any kind of optimization.
Information Geometry : Near Randomness and Near Independence
This volume will be useful to practising scientists and students working in the application of statistical models to real materials or to processes with perturbations of a Poisson process, a uniform process, or a state of independence for a bivariate process. We use information geometry to provide a common differential geometric framework for a wide range of illustrative applications including amino acid sequence spacings in protein chains, cryptology studies, clustering of communications and galaxies, cosmological voids, coupled spatial statistics in stochastic fibre networks and stochastic porous media, quantum chaology. Introduction sections are provided to mathematical statistics, differential geometry and the information geometry of spaces of probability density functions.
Information criteria and statistical modeling
One of the main objectives of this book is to provide comprehensive explanations of the concepts and derivations of the AIC and related criteria, including Schwarz’s Bayesian information criterion (BIC), together with a wide range of practical examples of model selection and evaluation criteria. A secondary objective is to provide a theoretical basis for the analysis and extension of information criteria via a statistical functional approach. A generalized information criterion (GIC) and a bootstrap information criterion are presented, which provide unified tools for modeling and model evaluation for a diverse range of models, including various types of nonlinear models and model estimation procedures such as robust estimation, the maximum penalized likelihood method and a Bayesian approach.
Information and knowledge : A constructive type-theoretical approach
This book develops a philosophical and logical interpretation of the concept of information within the formal structure of Constructive Type Theory (CTT), in a manner concurrent with a diverse range of contemporary perspectives on the philosophy of information. On the basis of this conceptual framework, the problem of analyticity for logical derivations is faced and a solution is proposed.The text begins with a presentation of the formal structure of CTT, paying particular attention to some topics that have been neglected by current researchers in Type Theory. Information and Knowledge presents a new interesting perspective on the constructive interpretation of knowledge processes, suggesting the reliability of such an approach for the logical modeling of epistemic problems and proposing a unifying frame from one of the more important contemporary philosophical perspectives.
Infinite matrices and their finite sections : An introduction to the limit operator method
In this book we are concerned with the study of a certain class of infinite matrices and two important properties of them: their Fredholmness and the stability of the approximation by their finite truncations. Let us take these two properties as a starting point for the big picture that shall be presented in what follows. Stability Fredholmness We think of our infinite matrices as bounded linear operators on a Banach space E of two-sided infinite sequences.The class of operators we are interested in consists of those bounded and linear operatorson E which can be approximated in the operator norm by b and matrices. We refer to them as band-dominated operators. Of course, these considerations 2 are not limited to the space E = . We will widen the selection of the underlying space E in three directions: p
Infinite groups : geometric, combinatorial and dynamical aspects
This book offers a panorama of recent advances in the theory of infinite groups. It contains survey papers contributed by leading specialists in group theory and other areas of mathematics. Topics addressed in the book include amenable groups, Kaehler groups, automorphism groups of rooted trees, rigidity, C*-algebras, random walks on groups, pro-p groups, Burnside groups, parafree groups, and Fuchsian groups. The accent is put on strong connections between group theory and other areas of mathematics, such as dynamical systems, geometry, operator algebras, probability theory, and others.
Infinite Dimensional Analysis : A Hitchhiker's Guide
This new edition of The Hitchhiker’s Guide has bene?tted from the comments of many individuals, which have resulted in the addition of some new material, and the reorganization of some of the rest. The most obvious change is the creation of a separate Chapter 7 on convex analysis. Parts of this chapter appeared in elsewhere in the second edition, but much of it is new to the third edition. In particular, there is an expanded discussion of support points of convex sets, and a new section on subgradients of convex functions.
Infinite dimensional algebras and quantum integrable systems
This volume presents the invited lectures of the workshop "Infinite Dimensional Algebras and Quantum Integrable Systems'' .ecent developments in the theory of infinite dimensional algebras and their applications to quantum integrable systems are reviewed by some of the leading experts in the field. The volume will be of interest to a broad audience from graduate students to researchers in mathematical physics and related fields.
Inference in Hidden Markov Models
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states.In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models.
Inference for change point and post change means after a CUSUM test
This monograph is the first to systematically study the bias of estimators and construction of corrected confidence intervals for change-point and post-change parameters after a change is detected by using a CUSUM procedure. Researchers in change-point problems and sequential analysis, time series and dynamic systems, and statistical quality control will find that the methods and techniques are mostly new and can be extended to more general dynamic models where the structural and distributional parameters are monitored. Practitioners, who are interested in applications to quality control, dynamic systems, financial markets, clinical trials and other areas, will benefit from case studies based on data sets from river flow, accident interval, stock prices, and global warming. Readers with an elementary probability and statistics background and some knowledge of CUSUM procedures will be able to understand most results as the material is relatively self-contained.The exponential family distribution is used as the basic model that includes changes in mean, variance, and hazard rate as special cases. There are fundamental differences between the sequential sampling plan and fixed sample size. Although the results are given under the CUSUM procedure, the methods and techniques discussed provide new approaches to deal with inference problems after sequential change-point detection, and they also contribute to the theoretical aspects of sequential analysis. Many results are of independent interests and can be used to study random walk related stochastic models.
Inductive logic programming ; 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers
The 18th International Conference on Inductive Logic Programming was held in Prague, September 10–12, 2008. ILP returned to Prague after 11 years, and it is tempting to look at how the topics of interest have evolved during that time. The ILP community clearly continues to cherish its beloved ?rst-order logic representation framework. This is legitimate, as the work presented at ILP 2008 demonstrated that there is still room for both extending established ILP approaches (such as inverse entailment) and exploring novel logic induction frameworks (such as brave induction). Besides the topics lending ILP research its unique focus.
Induction, Algorithmic Learning Theory, and Philosophy
This is the first book to collect essays from philosophers, mathematicians and computer scientists working at the exciting interface of algorithmic learning theory and the epistemology of science and inductive inference. Readable, introductory essays provide engaging surveys of different, complementary, and mutually inspiring approaches to the topic, both from a philosophical and a mathematical viewpoint.
Individual differences in sensory and consumer science : Experimentation, analysis and interpretation
Individual differences in sensory and consumer science: Experimentation, Analysis and Interpretation presents easily readable, State-of-the-art coverage on how to plan and execute experiments that give rise to individual differences, Also providing the framework for successful analysis and interpretation of results. The book highlights the different methodologies that can be applied and how to select the correct methodology based on the type of study you are performing, Be it product research and development, Quality control or consumer acceptance studies.Written by an experienced team of statisticians and sensory and consumer scientists, The book provides both academics and industry professionals with the first complete overview of a topic of ever-increasing importance.
