Михальский А.И. Machine learning в геронтологии

Из серии Foundations and Trends in Machine Learning издательства NOWPress, 2008, -163 pp. This paper describes a novel machine learning framework for solving sequential decision problems called Markov decision processes (MDPs) by iteratively computing low-dimensional representations and approximately optimal policies. A unified mathematical framework for learning representation and optimal control in MDPs is presented based on a class of singula...

Издательство Springer, 2008, -256 pp. The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. With first papers dating back to the 1960’s, DAR is a mature but still growing research field with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized products of the research in this field, while...

Издательство InTech, 2009, -430 pp. Machine Learning is often referred to as a branch of artificial intelligence which deals with the design and the development of algorithms and techniques that help machines to learn. Hence, it is closely related to various scientific domains as Optimization, Vision, Robotic and Control, Theoretical Computer Science, etc. Based on this, Machine Learning can be defined in various ways related to a scientific do...

This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning. 1997, р. 414. The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience. In recent years m...

Издательство Springer, 2011, -1058 pp. The term Machine Learning came into wide-spread use following the first workshop by that name, held at Carnegie-Mellon University in 1980. The papers from that workshop were published as Machine Learning: An Artificial Intelligence Approach, edited by Ryszard Michalski, Jaime Carbonell and Tom Mitchell. Machine Learning came to be identified as a research field in its own right as the workshops evolved into...

Издательство CRC Press, 2010, -218 pp. The problem of learning in dynamic environments is important and challenging. In the 1960s, learning from control of dynamical systems was studied extensively. At that time, learning was similar in meaning to other terms such as adaptation and self-organizing. Since the 1970s, learning theory has become a research discipline in the context of machine learning, and more recently as computational or statistic...

Издательство Idea Group, 2007, -384 pp. Machine learning is the study of how to build computer programs that improve their performance at some task through experience. The hallmark of machine learning is that it results in an improved ability to make better decisions. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fe...

Издательство InTech, 2010, -288 pp. In recent years many successful machine learning applications have been developed, ranging from data mining programs that learn to detect fraudulent credit card transactions, to information filtering systems that learn user’s reading preferences, to autonomous vehicles that learn to drive on public highways. At the same time, machine learning techniques such as rule induction, neural networks, genetic learnin...

Издательство InTech, 2010, -446 pp. The goal of this book is to present the key algorithms, theory and applications that from the core of machine learning. Learning is a fundamental activity. It is the process of constructing a model from complex world. And it is also the prerequisite for the performance of any new activity and, later, for the improvement in this performance. Machine learning is concerned with constructing computer programs tha...

Издательство InTech, 2010, -374 pp. The purpose of this book is to provide an up-to-data and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call Learning tasks, as we use the word in daily life. It is also broad enough to encompass computer that improve from experience in quite straight forward ways. Machine learning addresses the...