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Ryan Adams, I'm Gonna Run From You
Recently, numerous women have spoken out about their romantic relationships with singer/songwriter, Ryan Adams. This is my nightmare with Ryan Adams. This is a must read for every fan, but be cautioned, it may be difficult to process if you are indeed a fan. Everyone should find this book unsettling.
Patterns of Scalable Bayesian Inference
Identifies unifying principles, patterns, and intuitions for scaling Bayesian inference. Reviews existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, it characterizes the general principles that have proven successful for designing scalable inference procedures.
Bayesian Optimization
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.
Best of Ryan Adams
A group of resourceful kids start "solution-seekers.com," a website where "cybervisitors" can get answers to questions that trouble them. But when one questioner asks the true meaning of Christmas, the kids seek to unravel the mystery by journeying back through the prophecies of the Old Testament. What they find is a series of "S" words that reveal a "spectacular story!" With creative characters, humorous dialogue and great music, The "S" Files is a children's Christmas musical your kids will love performing.
From Artificial Intelligence to Brain Intelligence
Research in Artificial Intelligence (AI) is not new, it has been around since 1950’s. AI resurfaced at that time while Moore’s law was on an aggressive path of scaling, with the transformation of NMOS and later bipolar technology to CMOS for high performance, low power as well as low cost applications.Several breakthroughs in the electronics industry helped to push Moore’s law in chip miniaturization along with increased computing power (parallel and distributed processing) and memory bandwidth. Once this paradigm shift occurred it naturally opened doors for AI as it required big data manipulations, and thus AI could thrive again. AI has already shown success in industries such as fina...
Machine Learning
Presents carefully selected supervised and unsupervised learning methods from basic to state-of-the-art,in a coherent statistical framework.
The Marcusean Mind
Herbert Marcuse (1898–1979) was a member of the Frankfurt School, a leading figure of 1960s counterculture, and a fundamental character for the New Left. His ideas and theories, inspired by a rich fusion of Marxian and Freudian thought, exert a strong influence on contemporary thinking about activism, emancipation, and political resistance. He was also a student of Martin Heidegger in the late 1920s and engaged deeply with philosophy throughout his career. The Marcusean Mind is an outstanding survey and assessment of Marcuse's thought. Beginning with a thorough introduction to Marcuse's life and work, 39 chapters by an international and interdisciplinary team of contributors are organized ...
Fit
Why architecture matters—and how to make it matter more Fit is a book about architecture and society that seeks to fundamentally change how architects and the public think about the task of design. Distinguished architect and urbanist Robert Geddes argues that buildings, landscapes, and cities should be designed to fit: fit the purpose, fit the place, fit future possibilities. Fit replaces old paradigms, such as form follows function, and less is more, by recognizing that the relationship between architecture and society is a true dialogue—dynamic, complex, and, if carried out with knowledge and skill, richly rewarding. With a tip of the hat to John Dewey, Fit explores architecture as we...
Machine Learning for Computer Vision
Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. A summary of the past Computer Vision Summer Schools can be found at: http://www.dmi.unict.it/icvss This edited volume contains a selection of articles covering some of the talks and tutorials held during the last editions of the school. The chapters provide an in-depth overview of challenging areas with key references to the existing literature.
Automated Machine Learning and Meta-Learning for Multimedia
This book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciting and fast-growing research directions in the general field of machine learning. The authors advocate novel, high-quality research findings, and innovative solutions to the challenging problems in AutoML and meta-learning. This topic is at the core of the scope of artificial intelligence, and is attractive to audience from both academia and industry. This book is highly accessible to the whole machine learning community, including: researchers, students and practitioners who are interested in AutoML, meta-learning, and their applications in multimedia, computer vision, natural language processing and data mining related tasks. The book is self-contained and designed for introductory and intermediate audiences. No special prerequisite knowledge is required to read this book.
