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Action! Humor! Fantasy! "Kicking off a new series with a bang (several bangs, in fact), Stroud sends two young fugitives with murky pasts fleeing murderous pursuers across a fractured future Britain." —Kirkus Reviews, starred **Soon to be a motion picture starring Phoebe Dynevor of Bridgerton!** Scarlett McCain is a shoot-first ask-questions-later kind of outlaw. She scrapes by on bank heists, her wits—and never looking back. She’s on the run from her latest crime when she comes across Albert Browne. He is the sole survivor of a horrific accident, and against her better judgement, Scarlett agrees to guide him to safety. This is a mistake. Soon there are men with dogs and guns and explo...
Directed by Jonathan Glazer (Sexy Beast, Birth) and starring Scarlett Johansson, the 2013 film Under the Skin contains elements of science fiction and fantasy, horror, mystery, and thriller. Arguably the most compelling of Johansson's career, the movie follows a unique tale of one woman's journey to self-discovery. This is the first book to be written about the quiet masterpiece, revisiting the film scene-by-scene through all its cinematic elements. Extensive interviews detail the challenges the filmmakers faced--from hidden filming on the streets of Glasgow to defying a blizzard in the Scottish Highlands. Readers are invited to explore connections between the movie and its science fiction cousins and discover the reasons why Under the Skin deserves to find a wider audience.
Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond. This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way. This bottom-up approach illuminates unifying themes in the design of Bayesian optimization algorithms and builds a solid theoretical foundation for approaching novel situations. The core of the book is divided into three main parts, covering theoretical and practical aspects of Gaussian process modeling, the Bayesian approach to sequential decision making, and the realization and computation of practical and effective optimization policies. Following this foundational material, the book provides an overview of theoretical convergence results, a survey of notable extensions, a comprehensive history of Bayesian optimization, and an extensive annotated bibliography of applications.
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Dorchester annexed to Boston, Jan. 3, 1870; Roxbury annexed to Boston, Jan. 5, 1868.