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High-Dimensional Statistics
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Graphical Models, Exponential Families, and Variational Inference
The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.
Statistical Learning with Sparsity
Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl
High-Dimensional Statistics
Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.
Climate Leviathan
**Winner of the 2019 Sussex International Theory Prize** -- How climate change will affect our political theory - for better and worse Despite the science and the summits, leading capitalist states have not achieved anything close to an adequate level of carbon mitigation. There is now simply no way to prevent the planet breaching the threshold of two degrees Celsius set by the Intergovernmental Panel on Climate Change. What are the likely political and economic outcomes of this? Where is the overheating world heading? To further the struggle for climate justice, we need to have some idea how the existing global order is likely to adjust to a rapidly changing environment. Climate Leviathan provides a radical way of thinking about the intensifying challenges to the global order. Drawing on a wide range of political thought, Joel Wainwright and Geoff Mann argue that rapid climate change will transform the world's political economy and the fundamental political arrangements most people take for granted. The result will be a capitalist planetary sovereignty, a terrifying eventuality that makes the construction of viable, radical alternatives truly imperative.
Advances in Neural Information Processing Systems 19
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
High-Dimensional Probability
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
Computer Age Statistical Inference, Student Edition
Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.
Bandit Algorithms
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Virtual History
Virtual History examines many of the most popular historical video games released over the last decade and explores their portrayal of history. The book looks at the motives and perspectives of game designers and marketers, as well as the societal expectations addressed, through contingency and determinism, economics, the environment, culture, ethnicity, gender, and violence. Approaching videogames as a compelling art form that can simultaneously inform and mislead, the book considers the historical accuracy of videogames, while also exploring how they depict the underlying processes of history and highlighting their strengths as tools for understanding history. The first survey of the historical content and approach of popular videogames designed with students in mind, it argues that games can depict history and engage players with it in a useful way, encouraging the reader to consider the games they play from a different perspective. Supported by examples and screenshots that contextualize the discussion, Virtual History is a useful resource for students of media and world history as well as those focusing on the portrayal of history through the medium of videogames.
