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Artificial Intelligence and Machine Learning
This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML. Artificial Intelligence (AI) is a broad area of knowledge which has percolated into every aspect of human life. ‘Machine Learning algorithms’ are considered to be a subset of AI Theory, mathematics and coding are three aspects to any topic in AI. This book covers the most relevant topics in the field of Artificial Intelligence and Machine Learning (ML). The subdivisions of Machine Learning are Supervised, Unsupervised and Reinforcement learning. All three are covered in sufficient depth. One very important and upcoming field of application is ...
Progress in VLSI Design and Test
This book constitutes the refereed proceedings of the 16th International Symposium on VSLI Design and Test, VDAT 2012, held in Shibpur, India, in July 2012. The 30 revised regular papers presented together with 10 short papers and 13 poster sessions were carefully selected from 135 submissions. The papers are organized in topical sections on VLSI design, design and modeling of digital circuits and systems, testing and verification, design for testability, testing memories and regular logic arrays, embedded systems: hardware/software co-design and verification, emerging technology: nanoscale computing and nanotechnology.
Sequential Analysis
Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently. The book reviews recent accomplishments in hypothesis testing and changepoint detecti
Partially Observed Markov Decision Processes
Covering formulation, algorithms, and structural results, and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. Bringing together research from across the literature, the book provides an introduction to nonlinear filtering followed by a systematic development of stochastic dynamic programming, lattice programming and reinforcement learning for POMDPs. Questions addressed in the book include: when does a POMDP have a threshold optimal policy? When are myopic policies optimal? How do local and global decision makers interact in adaptive decision making in multi-agent social learning where there is herding and data incest? And how can sophisticated radars and sensors adapt their sensing in real time?
Arab-Islamic Biographical Index
The biographical indexes, part of the World Biographical Information System (WBIS) and used as indexes for the biographical archives, serve as an independent biographical research tool, with each index containing short biographical entries on individuals relating to a certain biographical or cultural region, and each entry including names, biographical data, professions and evaluated sources. The Arab-Islamic Biographical Index contains summarised information on around 80,000 individuals from the pre-Islamic period until 1918. It includes not only individuals who were born in the region, but also foreigners who were active within it.
Robustness
The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
