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The Student Loan Scam
In this in-depth exploration and expos of the predatory nature of the student loan industry, Collinge argues that student loans have become the most uncompetitive and oppressive type of debt in American history. In this clarion call for social action, the author offers pragmatic solutions.
Handbook of Computational Social Science for Policy
This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing...
Studies in Neural Data Science
This volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain imaging data. During this meeting, which was held on June 25–27, 2017 in Siena (Italy), the research groups focused on recent multimodality imaging datasets measuring brain function and structure, and proposed a wide variety of methods for network analysis, spatial inference, graphical modeling, multiple testing, dynamic inference, data fusion, tensor factorization, object-oriented analysis and others. The results of their studies are gathered here, along with a final contribution by Michele Guindani and Marina Vannucci that opens new research directions in this field. The book offers a valuable resource for all researchers in Data Science and Neuroscience who are interested in the promising intersections of these two fundamental disciplines.
Algorithmic Learning in a Random World
This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature of conformal prediction is the principled treatment of the reliability of predictions. The prediction algorithms described — conformal predictors — are provably valid in the sense that they evaluate the reliability of their own predictions in a way that is neither over-pessimistic nor over-optimistic (the latter being especially dangerous). The approach is still flexible enough to incorporate most of the existing powerful methods of machine learning. The book covers both key conformal predictors and the mathematical analysis of their properties. Algor...
A Season With Verona
'Delves into the very essence of being a fan, while seamlessly exploring Italian history, politics, culture and society,' Guardian Is Italy a united country, or a loose affiliation of warring states? Is Italian football a sport, or an ill-disguised protraction of ancient enmities? Tim Parks goes on the road to follow the fortunes of Hellas Verona football club, to pay a different kind of visit to some of the world's most beautiful cities. This is a highly personal account of one man's relationship with a country, its people and its national sport. A book that combines the pleasures of travel writing with a profound analysis of one country's mad, mad way of keeping itself entertained.
Functional and High-Dimensional Statistics and Related Fields
This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recogni...
