Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Pragmatic C
None
Pragmatic C
None
Pragmatic C
None
Gaussian Processes for Machine Learning
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both ...
Immunohistochemical Expression
Immunohistochemistry (IHC) is an ancillary method, widely used in pathologists’ practice, that allows identifying diagnostic and prognostic/predictive of therapeutic response protein markers on tissue samples by the use of specific monoclonal antibodies and chromogenic substances that guarantee the visualization of an antibody–antigene binding complex under a light microscope [1]. Coon et al., in 1941 [2], first introduced the use of fluorochrome-conjugated antibodies in clinical practice. Since then, IHC has gone from being a useful tool for identifying the differentiation line of otherwise undifferentiated cells to a technique capable of providing not only diagnostic but also prognostic and predictive indications of responses to specific therapeutic options [1,3]. The abovementioned peculiarities have made IHC one of the most used ancillary methods in the histopathological approach to human neoplastic and non-neoplastic diseases [3-5]. This Special Issue contains 11 accepted papers that provide readers with a comprehensive update on current and future applications of IHC in medical practice.
Multi-Objective Decision Making
Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decisi...
