Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite po...
This new and expanded edition is intended to help candidates prepare for entrance examinations in mathematics and scientific subjects, including STEP (Sixth Term Examination Paper). STEP is an examination used by Cambridge Colleges for conditional offers in mathematics. They are also used by some other UK universities and many mathematics departmen...
The use of non-standard technologies such as superconductivity, cryogenics and radiofrequency pose challenges for the safe operation of accelerator facilities that cannot be addressed using only best practice from occupational safety in conventional industry. This book introduces readers to different occupational safety issues at accelerator facili...
This open book presents selected papers from International Symposium on Mathematics, Quantum Theory, and Cryptography (MQC), which was held on September 25-27, 2019 in Fukuoka, Japan. The international symposium MQC addresses the mathematics and quantum theory underlying secure modeling of the post quantum cryptography including e.g. mathematical s...
This open book focuses on robot introspection, which has a direct impact on physical human - robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is...
This open book presents new developments in the field of demographic forecasting, covering both mortality, fertility and migration. For each component emerging methods to forecast them are presented. Moreover, instruments for forecasting evaluation are provided. Bayesian models, nonparametric models, cohort approaches, elicitation of expert opinion...
This open book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introdu...
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges an...
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them.
Automated decision-making systems or decision-support systems - used in applications that range from aircraft collision avoidance to breast cancer screening - must be designed...
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamen...
Network and System Administration usually refers only to the traditional skills and recipes for keeping computers and networks running properly. But, in truth, this view omits the most important part of the system: humans. The skill needed to comprehend and tame systems comprising both humans and machines is that of managing complexity. In this boo...
This is an image processing textbook with a difference. Instead of just a picture gallery of before-and-after images, we provide (on the accompanying website) MATLAB programs (.m files) and images (.mat files) for each of the examples. These allow the reader to experiment with various parameters, such as noise strength, and see their effect on the ...