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Adland
Adland is a ground-breaking examination of modern advertising, from its early origins, to the evolution of the current advertising landscape. Bestselling author and journalist Mark Tungate examines key developments in advertising, from copy adverts, radio and television, to the opportunities afforded by the explosion of digital media - podcasting, text messaging and interactive campaigns. Adland focuses on key players in the industry and features exclusive interviews with leading names in advertising today, including Jean-Marie Dru, Sir Alan Parker, John Hegarty and Sir Martin Sorrell, as well as industry luminaries from the 20th Century such as Phil Dusenberry and George Lois. Exploring the roots of the advertising industry in New York and London, and going on to cover the emerging markets of Eastern Europe, Asia and Latin America, Adland offers a comprehensive examination of a global industry and suggests ways in which it is likely to develop in the future.
Nine Mathematical Challenges: An Elucidation
This volume stems from the Linde Hall Inaugural Math Symposium, held from February 22–24, 2019, at California Institute of Technology, Pasadena, California. The content isolates and discusses nine mathematical problems, or sets of problems, in a deep way, but starting from scratch. Included among them are the well-known problems of the classification of finite groups, the Navier-Stokes equations, the Birch and Swinnerton-Dyer conjecture, and the continuum hypothesis. The other five problems, also of substantial importance, concern the Lieb–Thirring inequalities, the equidistribution problems in number theory, surface bundles, ramification in covers and curves, and the gap and type problems in Fourier analysis. The problems are explained succinctly, with a discussion of what is known and an elucidation of the outstanding issues. An attempt is made to appeal to a wide audience, both in terms of the field of expertise and the level of the reader.
Abolition
The English translation of a behind-the-scenes account of the abolition of the death penalty in France
Number Theory, Analysis and Geometry
Serge Lang was an iconic figure in mathematics, both for his own important work and for the indelible impact he left on the field of mathematics, on his students, and on his colleagues. Over the course of his career, Lang traversed a tremendous amount of mathematical ground. As he moved from subject to subject, he found analogies that led to important questions in such areas as number theory, arithmetic geometry, and the theory of negatively curved spaces. Lang's conjectures will keep many mathematicians occupied far into the future. In the spirit of Lang’s vast contribution to mathematics, this memorial volume contains articles by prominent mathematicians in a variety of areas of the field, namely Number Theory, Analysis, and Geometry, representing Lang’s own breadth of interest and impact. A special introduction by John Tate includes a brief and fascinating account of the Serge Lang’s life. This volume's group of 6 editors are also highly prominent mathematicians and were close to Serge Lang, both academically and personally. The volume is suitable to research mathematicians in the areas of Number Theory, Analysis, and Geometry.
The Economics and Econometrics of Innovation
During the past few decades, the interest of economists in the sources of long-term economic growth has led an increasing number of them to focus on the role of innovation in creating that growth. Although some researchers have always been interested in this topic, the groundbreaking work of Solow (1957), Nelson (1959) and Arrow (1962) made many other economists recognize the central role played by innovation in almost all spheres of economic activity. The Economics and Econometrics of Innovation presents a valuable overview of the work of the world's most renowned experts in the field of innovation and technical change. It collects 22 outstanding contributions that reflect the results of th...
Machine Learning in Insurance
Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.
