Cognitive Computing: Theory and Applications

Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface.

A. Fundamentals and Principles 1. Cognitive Computing: Concepts, Architectures, Systems and Applications Venkat N Gudivada 2. Cognitive Computing and Neural Networks: Reverse Engineering the Brain Anthony S. Maida

B. Complex Analytics and Machine Learning 3. Visual Analytic Decision Making Environments for Large-Scale Time Evolving Graphs Siva R. Venna, Raju N. Gottumukkala and Vijay V. Raghavan 4. CyGraph: Graph-Based Analytics and Visualization for Cybersecurity Steven Noel, Eric Harley, Kam Him Tam, Michael Limiero and Matthew Share 5. Cognitive Analytics: Going Beyond Big Data Analytics and Machine Learning Venkat N Gudivada, Mohammad T. Irfan, Ehsan Fathi and Dhana L Rao 6. A Cognitive Random Forest: An Intra- and Inter-Cognitive Computing for Big Data Classification Under Cune-Condition Shan Suthaharan 7. Bayesian Additive Regression Tree for Seemingly Unrelated Regression with Automatic Tree Selection Sounak Chakraborty

C. Applications 8. Cognitive Systems for the Food-Water-Energy Nexus Vincent P. A. Lonij and Jean-Baptiste Fiot 9. Cognitive Computing Applications in Education and Learning Mohammad T. Irfan and Venkat N Gudivada 10. Large Scale Data Enabled Evolution of Spoken Language Research and Applications S. Jothilakshmi and Venkat N Gudivada 11. The Internet of Things and Cognitive Computing Florence D. Hudson