Apr 16 2016 Added eBooks

Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of cl...

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential and Integral Calculus introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving a short introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work with ease in differential and integral c...

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: Explains how reputation-based systems are used to determine trust in diverse online communities Describes how machine learning techniques are employed to build robust reputation systems Explores two distinctive approaches to determining credibility of resourcesone where the human role is implicit, and one that leverages human input explicitly Shows how decision support can be facilitated by computational trust mo...

Malicious email is, simply put, email with a malicious purpose. The malicious purpose could be fraud, theft, espionage, or malware injection. The processes by which email execute the malicious activity vary widely, from fully manual (e.g. human-directed) to fully automated. One example of a malicious email is one that contains an attachment which the recipient is directed to open. When the attachment is opened, malicious software is installed on the recipient's computer. Because malicious email can vary so broadly in form and function, automated detection is only marginally helpful. The education of all users to detect potential malicious email is important to containing the threat and limiting the damage. It is increasingly necessary for all email u...