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The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representati...
Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these issues of dimensionality reduction, finds widespread
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
Information security cannot be effectively managed unless secure methods and standards are integrated into all phases of the information security life cycle. And, although the international community has been aggressively engaged in developing security standards for network and information security worldwide, there are few textbooks available that
An authoritative treatment of urban computing, offering an overview of the field, fundamental techniques, advanced models, and novel applications. Urban computing brings powerful computational techniques to bear on such urban challenges as pollution, energy consumption, and traffic congestion. Using today's large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science with urban planning, transportation, environmental science, sociology, and other areas of urban studies, tackling specific problems with concrete methodologies in a data-centric computing framework. This authoritative treatment of urban computing offers an overview o...
Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy.
The 2022 International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC 2022) was successfully held in Qingdao, China from June 17 to 19, 2022. Under the impact of COVID-19, ICIDC 2022 was held adopting a combination of online and offline conference. During this conference, we were greatly honored to have Prof Datuk Dr Hj Kasim Hj Md Mansur from Universiti Malaysia Sabah, Malaysia to serve as our Conference Chairman. And there were 260 individuals attending the conference. The conference agenda was composed of keynote speeches, oral presentations, and online Q&A discussion. The proceedings of ICIDC 2022 cover various topics, including Big Data Finance, E-Commerce a...
It is with great pleasure that I welcome you to Lake Tahoe for the 2005 Int- national Symposium on Visual Computing (ISVC). ISVC provides a common umbrella for the four main areas of visual computing: vision, graphics, visu- ization, and virtual reality. The goal of ISVC is to provide a common forum for researchers, scientists, engineers, and practitioners throughout the world to present their latest research ?ndings, ideas, developments, and applications in the broader area of visual computing. The program consists of six oral sessions, two poster sessions, seven special tracks,fourkeynotepresentations,andoneinvitedpresentation.Theresponseto thecallforpapersforthegeneralISVC2005sessionswasv...
This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Although the patch management process is neither exceedingly technical nor extremely complicated, it is still perceived as a complex issue that's often left to the last minute or resolved with products that automate the task. Effective patch management is not about technology; it's about having a formal process in place that can deploy patches to v