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Catalogue complet

Molchanov I: Risk Measures

Risk Measures

An Introduction to the Mathematical Theory

Cultivating Vitality, Presence, and Impact in a Changing World

Full Voice for Leaders

Modern Trends In Financial Engineering

This introductory/intermediate level textbook focuses on mathematical programming and its applications. It introduces basic linear programming -- the easiest form of mathematical programming with emphasis on economic interpretation of the model solution. Well-known applications of linear programming to problems in business and agriculture are presented.The text then extends into more advanced forms of mathematical programming including quadratic and integer programming. These models include the introduction of risk and uncertainty into decision-making and a class of models known as price endogenous models in which market equilibrium analyses can be modelled. Integer programming includes conditional decision-making model, machinery selection, and a class of models known as supply chain models.Supplements are provided to assist solution of the models using either GAMS or Excel, the two most widely used software packages for solution of mathematical programming models.

Applied Mathematical Programming For Business And Economics

Using AI for Intelligent Business Analytics

Transforming Digital Commerce

This book is the first one that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. They develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.

Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

Wiley Series in Probability and Statistics

New edition of a PROSE award finalist title on core concepts for machine learning, updated with the latest developments in the field, now with Python and R source code side-by-side Machine Learning is a comprehensive text on the core concepts, approaches, and applications of machine learning. It presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. New content for this edition includes chapter expansions which provide further computational and algorithmic insights to improve reader understanding. This edition also revises several chapters to account for developments since the prior edition. In this book, the design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods, enabling readers to solve applied problems more efficiently and effectively. This book also includes methods for optimization, risk estimation, model selection, and dealing with biased data samples and software limitations - essential elements of most applied projects. Written by an expert in the field, this important resource: <ul> <li>Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods</li> <li>Presents side-by-side Python and R source code which shows how to apply and interpret many of the techniques covered</li> <li>Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions</li> <li>Contains useful information for effectively communicating with clients on both technical and ethical topics</li> <li>Details classification techniques including likelihood methods, prototype methods, neural networks, classification trees, and support vector machines</li> </ul> A volume in the popular Wiley Series in Probability and Statistics, Machine Learning offers the practical information needed for an understanding of the methods and application of machine learning for advanced undergraduate and beginner graduate students, data science and machine learning practitioners, and other technical professionals in adjacent fields.

A Concise Introduction

Machine Learning

This book is intended to help people newly involved in the development of workplace safety and health programs to understand principles and concepts that can help them roll out what is often referred to as a "safety program". It introduces the safety and health landscape in simple terms and provides a framework for common program start-up or program improvement action steps.Providing small and medium sized enterprises (SMEs) with a primer on how to think about and go about creating a safety program, this book presents a higher-level overview, framework models and suggestions, resource information, and shares concepts that can help readers not only meet regulatory requirements but also provide true value to the organization. Safety consultant Greg G. Zigulis presents readers with an accessible overview of the types of things that should be known and considered in order to create and run an effective and sustainable health and safety program.Written for a broad professional readership, this book will be invaluable for all SME businesspersons and practitioners who need a seasoned expert to provide an understandable introduction to safety programs, whatever their situation. It's particularly relevant to start-ups and people given responsibility for workplace safety without a background in this area.

Setting Them Up and Making Them Work Effectively

Health and Safety Programs in Small and Medium-sized Businesses

How We Gave Computers the Power to Choose for Us

The Irrational Decision

National Bureau of Economic Research Studies in Income and Wealth

Race, Ethnicity, and Economic Statistics for the 21st Century

Encyclopedia of Optimization

Tools and Frameworks for Managing People Risk and Increasing Resilience

Fundamentals of People Risk Management

World Scientific Lecture Notes In Economics And Policy

This book attempts to understand the operation and properties of 'market economies'. We do this by carefully examining, refining and in some cases extending the major theorems that Microeconomics has established in response to the Walrasian conjecture. We critically evaluate theorems and results, that assert the existence, uniqueness, stability, optimality and empirical relevance of Walrasian equilibrium states. As a result of our work, we attempt to comment on the wisdom of recommending that socio-economic systems operate as a collection of deregulated competitive markets.

Lectures In General Equilibrium Microeconomics

Multiphysics: Advances and Applications

Thermoforming Modeling and Simulation: A Multiphysics Approach concentrates on the modeling and optimization of thermoforming, as well as identifying the structural behavior of thermoplastics used for thermoforming. The book demonstrates the expertise gained through industrial and academic projects in technical transfer. It also illustrates the research and development skills in experimental and numerical modeling of thermoforming. The problem of identifying laws of behavior from experimental data (rheological or mechanical tests in large deformations), using algorithms such as neural networks, is also addressed. Through its multiphysics content, this book is helpful for researchers, teachers and industrialists interested in new advances in thermoforming (characterization of materials, modeling and optimization).

A Multiphysics Approach

Thermoforming Modeling and Simulation

Risk Measures

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