Alexander Gammerman's Books

Algorithmic Learning in a Random World

By: Vladimir Vovk,Alexander Gammerman,Glenn Shafer

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Algorithmic Learning in a Random World

By: Vladimir Vovk,Alexander Gammerman,Glenn Shafer

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. Algorithmic Learning in a Random World contains, in addition to proofs of validity, results about the efficiency of conformal predictors. The only assumption required for validity is that of "randomness" (the prediction algorithm is presented with independent and identically distributed examples); in later chapters, even the assumption of randomness is significantly relaxed. Interesting results about efficiency are established both under randomness and under stronger assumptions. Since publication of the First Edition in 2005 conformal prediction has found numerous applications in medicine and industry, and is becoming a popular machine-learning technique. This Second Edition contains three new chapters. One is about conformal predictive distributions, which are more informative than the set predictions produced by standard conformal predictors. Another is about the efficiency of ways of testing the assumption of randomness based on conformal prediction. The third new chapter harnesses conformal testing procedures for protecting machine-learning algorithms against changes in the distribution of the data. In addition, the existing chapters have been revised, updated, and expanded.

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Page Count

490

Publisher

Springer Nature

Published Date

ISBN 10

3031066499

ISBN 13

9783031066498

Materials Science and Engineering

Chapter 3. Novel Approaches to Statistical Learning in Materials Science

By: F.J. Alexander,T. Lookman

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Materials Science and Engineering

Chapter 3. Novel Approaches to Statistical Learning in Materials Science

By: F.J. Alexander,T. Lookman

We describe developments in statistical learning theory and their application to problems in materials science. An example in the context of piezoelectrics is also discussed.

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Elsevier Inc. Chapters

Published Date

ISBN 10

0128059338

ISBN 13

9780128059333

Learning with Kernels

Support Vector Machines, Regularization, Optimization, and Beyond

By: Bernhard Scholkopf,Alexander J. Smola

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Learning with Kernels

Support Vector Machines, Regularization, Optimization, and Beyond

By: Bernhard Scholkopf,Alexander J. Smola

A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

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Page Count

645

Publisher

MIT Press

Published Date

ISBN 10

0262536579

ISBN 13

9780262536578

Chessie Racing

The Story of Maryland's Entry in the 1997-1998 Whitbread Round the World Race

By: George J. Collins,Kathy Alexander

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Chessie Racing

The Story of Maryland's Entry in the 1997-1998 Whitbread Round the World Race

By: George J. Collins,Kathy Alexander

The history of the racing yacht Chessie, the first ever entry from the Chesapeake Bay in the famous Whitbread Round the World Race. This book records the history of the racing yacht Chessie, the first ever entry from the Chesapeake Bay in the famous Whitbread Round the World Race. Skippered by Baltimore businessman George Collins and named after the Chesapeake's equivalent to the Loch Ness monster, Chessie became a focal point of regional and national pride when she competed in 1997-98. That year was also the first time that Baltimore and Annapolis were included as a combined stopover in the nine-leg, 31,600-mile race, beginning and ending in Southampton, England. After a neck-and-neck race up the bay against famed skipper Dennis Connor, Chessie entered Baltimore's Inner Harbor greeted by the cheers of thousands of fans. During the stopover, over a half-million visitors came to the Whitbread Race Village in Baltimore and an additional sixty thousand toured the Race Village in Annapolis, giving Baltimore-Annapolis the highest attendance of any of the nine ports visited by the race. While racing, the boat also served an educational purpose through a two-part curriculum developed by the Living Classrooms Foundation, a Baltimore nonprofit educational organization for at-risk children. Children from five hundred schools in twenty states and seven foreign countries participated through the Whitbread Education Project, a curriculum package augmented by an Internet component, the Chessie Chase, which explored academic subjects such as math, science, social studies, geography, and literature and tackled such practical issues as vessel design, ocean currents, changing weather, and the principles of navigation. Classes competed in a virtual race against each other in the multifaceted program for a chance to visit Chessie and meet her crew when she reached Baltimore. The children also exchanged e-mails with Chessie's crew throughout the race. When President Clinton and Vice President Gore visited the Living Classrooms Foundation in Baltimore, students helped them write an e-mail to the boat saying, "Have a great race." This book contains chapters on the race, boat construction, crew selection, and the Living Classrooms Foundation Whitbread Education Project. Personal experiences and memories of the crew bring the sailing adventure to life and reveal the educational purpose of the boat. Sidebars feature useful charts and information, special observations, and a few human-interest e-mail exchanges between individuals and the crew. A large Mercator-projection map marks the race course and individual legs. Numerous photos document racing action as well as the hoopla on shore.

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Page Count

252

Publisher

JHU Press

Published Date

ISBN 10

0801864135

ISBN 13

9780801864131

Book's by Alexander Gammerman

Algorithmic Learning in a Random World

Algorithmic Learning in a Random World

Materials Science and Engineering

Materials Science and Engineering

Learning with Kernels

Learning with Kernels

Chessie Racing

Chessie Racing

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