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An Introduction to Machine Learning
This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes.
Fundamentals of Artificial Intelligence: Problem Solving and Automated Reasoning
A hands-on introduction to the principles and practices of modern artificial intelligence This comprehensive textbook focuses on the core techniques and processes underlying today’s artificial intelligence, including algorithms, data structures, logic, automated reasoning, and problem solving. The book contains information about planning and about expert systems. Fundamentals of Artificial Intelligence: Problem Solving and Automated Reasoning is written in a concise format with a view to optimizing learning. Each chapter contains a brief historical overview, control questions to reinforce important concepts, plus computer assignments and ideas for independent thought. The book includes many visuals to illustrate the essential ideas and many examples to show how to use these ideas in practical implementations. Presented in a concise format to optimize learning Includes historical overviews, summaries, exercises, thought experiments, and computer assignments Written by a recognized artificial intelligence expert and experienced author
Machines that Learn to Play Games
The mind-set that has dominated the history of computer game playing relies on straightforward exploitation of the available computing power. The fact that a machine can explore millions of variations sooner than the sluggish human can wink an eye has inspired hopes that the mystery of intelligence can be cracked, or at least side-stepped, by sheer force. Decades of the steadily growing strength of computer programs have attested to the soundness of this approach. It is clear that deeper understanding can cut the amount of necessary calculations by orders of magnitude. The papers collected in this volume describe how to instill learning skills in game playing machines. The reader is asked to keep in mind that this is not just about games -- the possibility that the discussed techniques will be used in control systems and in decision support always looms in the background.
Machine Learning and Data Mining
Master the new computational tools to get the most out of your information system. This practical guide, the first to clearly outline the situation for the benefit of engineers and scientists, provides a straightforward introduction to basic machine learning and data mining methods, covering the analysis of numerical, text, and sound data.
Machine Learning: ECML'97
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues.
Machine Learning: ECML-95
This volume constitutes the proceedings of the Eighth European Conference on Machine Learning ECML-95, held in Heraclion, Crete in April 1995. Besides four invited papers the volume presents revised versions of 14 long papers and 26 short papers selected from a total of 104 submissions. The papers address all current aspects in the area of machine learning; also logic programming, planning, reasoning, and algorithmic issues are touched upon.
Machine Learning: ECML-93
This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.
American Men and Women in Medicine, Applied Sciences and Engineering with Roots in Czechoslovakia
No comprehensive study has been undertaken about the American learned men and women with Czechoslovak roots. The aim of this work is to correct this glaring deficiency, with the focus on men and women in medicine, applied sciences and engineering. It covers immigration from the period of mass migration and beyond, irrespective whether they were born in their European ancestral homes or whether they have descended from them. This compendium clearly demonstrates the Czech and Slovak immigrants, including Bohemian Jews, have brought to the New World, in these areas, their talents, their ingenuity, the technical skills, their scientific knowhow, as well as their humanistic and spiritual upbringi...
Maneuverable Formation Control in Constrained Space
Inspired by the community behaviors of animals and humans, cooperative control has been intensively studied by numerous researchers in recent years. Cooperative control aims to build a network system collectively driven by a global objective function in a distributed or centralized communication network and shows great application potential in a wide domain. From the perspective of cybernetics in network system cooperation, one of the main tasks is to design the formation control scheme for multiple intelligent unmanned systems, facilitating the achievements of hazardous missions – e.g., deep space exploration, cooperative military operation, and collaborative transportation. Various chall...
Intelligent Problem Solving. Methodologies and Approaches
The focus of the papers presented in these proceedings is on employing various methodologies and approaches for solving real-life problems. Although the mechanisms that the human brain employs to solve problems are not yet completely known, we do have good insight into the functional processing performed by the human mind. On the basis of the understanding of these natural processes, scientists in the field of applied intelligence have developed multiple types of artificial processes, and have employed them successfully in solving real-life problems. The types of approaches used to solve problems are dependant on both the nature of the problem and the expected outcome. While knowledge-based ...
