To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
What happens to risk as the economic horizon goes to zero and risk is seen as an exposure to a change in state that may occur instantaneously at any time? All activities that have been undertaken statically at a fixed finite horizon can now be reconsidered dynamically at a zero time horizon, with arrival rates at the core of the modeling. This book, aimed at practitioners and researchers in financial risk, delivers the theoretical framework and various applications of the newly established dynamic conic finance theory. The result is a nonlinear non-Gaussian valuation framework for risk management in finance. Risk-free assets disappear and low risk portfolios must pay for their risk reduction with negative expected returns. Hedges may be constructed to enhance value by exploiting risk interactions. Dynamic trading mechanisms are synthesized by machine learning algorithms. Optimal exposures are designed for option positioning simultaneously across all strikes and maturities.
This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
This pioneering volume explores the long-neglected history of social rights, from the Middle Ages to the present. It debunks the myth that social rights are 'second-generation rights' – rights that appeared after World War II as additions to a rights corpus stretching back to the Enlightenment. Not only do social rights stretch back that far; they arguably pre-date the Enlightenment. In tracing their long history across various global contexts, this volume reveals how debates over social rights have often turned on deeper struggles over social obligation – over determining who owes what to whom, morally and legally. In the modern period, these struggles have been intertwined with questions of freedom, democracy, equality and dignity. Many factors have shaped the history of social rights, from class, gender and race to religion, empire and capitalism. With incomparable chronological depth, geographical breadth and conceptual nuance, Social Rights and the Politics of Obligation in History sets an agenda for future histories of human rights.
Sidney Coleman (1937–2007) earned his doctorate at Caltech under Murray Gell-Mann. Before completing his thesis, he was hired by Harvard and remained there his entire career. A celebrated particle theorist, he is perhaps best known for his brilliant lectures, given at Harvard and in a series of summer school courses at Erice, Sicily. Three times in the 1960s he taught a graduate course on Special and General Relativity; this book is based on lecture notes taken by three of his students and compiled by the Editors.
We are currently witnessing some of the greatest challenges to democratic regimes since the 1930s, with democratic institutions losing ground in numerous countries throughout the world. At the same time organized labor has been under assault worldwide, with steep declines in union density rates. In this timely handbook, scholars in law, political science, history, and sociology explore the role of organized labor and the working class in the historical construction of democracy. They analyze recent patterns of democratic erosion, examining its relationship to the political weakening of organized labor and, in several cases, the political alliances forged by workers in contexts of nationalist or populist political mobilization. The volume breaks new ground in providing cross-regional perspectives on labor and democracy in the United States, Europe, Latin America, Africa, and Asia. Beyond academia, this volume is essential reading for policymakers and practitioners concerned with the relationship between labor and democracy.