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Hierarchical Bayesian Optimization Algorithm : Toward a New Generation of Evolutionary Algorithms
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope.
Hands-on question answering systems with BERT : Applications in neural networks and natural language processing
Begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. You will: Examine the fundamentals of word embeddings / Apply neural networks and BERT for various NLP tasks / Develop a question-answering system from scratch / Train question-answering systems for your own data
Explosively Driven Pulsed Power : Helical Magnetic Flux Compression Generators
While the basic operating principles of Helical Magnetic Flux Compression Generators are easy to understand, the details of their construction and performance limits have been described only in government reports, many of them classified. Conferences in the field of flux compression are also dominated by contributions from government (US and foreign) laboratories. And the government-sponsored research has usually been concerned with very large generators with explosive charges that require elaborate facilities and safety arrangements. This book emphasizes research into small generators (less than 500 grams of high explosives) and explains in detail the physical fundamentals, construction details, and parameter-variation effects related to them.
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Linear Genetic Programming
Linear Genetic Programming examines the evolution of imperative computer programs written as linear sequences of instructions. In contrast to functional expressions or syntax trees used in traditional Genetic Programming (GP), Linear Genetic Programming (LGP) employs a linear program structure as genetic material whose primary characteristics are exploited to achieve acceleration of both execution time and evolutionary progress.
Calculus : One and several variables
Provides clear calculus content to help them master these concepts and understand its relevance to the real world. Throughout the pages, it offers a perfect balance of theory and applications to elevate their mathematical insights. Readers will also find that the book emphasizes both problem-solving skills and real-world applications.
Bluetooth based indoor location positioning system for mobile robot navigation
Positioning objects has been an important topic since it’s needed to locate people, guide them to a certain place, and assist companies and organizations with their assets management. Great applicational opportunities emerge based on the inquiry of Received Signal Strength Indicator (RSSI). In this research, a positioning system using Bluetooth RSSI is proposed for indoor applications. First, RSSI values are inquired multiple times and the average is taken at multiple points of different distances from the transmitters. Then the distance is determined by the variations of RSSI values respectively to distance variations. Finally, a triangulation algorithm is used to calculate the current location of the receiver.
Basic Coastal Engineering
Basic Coastal Engineering, 3rd Edition offers the basics on monochromatic and spectral surface wave mechanics, coastal water level variations, coastal structures and coastal sedimentary processes. It also provides the necessary background from which the reader can pursue a more advanced study of the various theoretical and applied aspects of coastal hydrodynamics and design.
Analysis and Modeling of Faces and Gestures ; 3rd International Workshop, AMFG 2007 Rio de Janeiro, Brazil, October 20, 2007 Proceedings
The book covered by these accepted papers include feature representation, 3D face, robust recognition under pose and illumination variations,video-basedface recognition,learning,facial motion analysis, body pose estimation, and sign recognition.
An Invitation to Statistics in Wasserstein Space
This book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation.
