This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods. Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).
This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social networks; temporal and spatial databases; and graph data and road networks. The papers of the second volume discuss a range of the following topics: Information retrieval; uncertain information; data warehouses and recommender systems; data streams; information networks and algorithms; database system architecture and performance; novel database solutions; graph querying and databases; learning; emerging applications; data mining; privacy; and text processing.
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
This book constitutes the refereed proceedings of the 32nd International Symposium on Computer and Information Sciences, ISCIS 2018, held in Poznan, Poland, in September 2018. The 29 revised full papers presented were carefully reviewed and selected from 64 submissions. The papers are dealing with the following topics: smart algorithms; data classification and processing; stochastic modelling; performance evaluation; queuing systems; wireless networks and security; image processing and computer vision.
Volume 1 of 'The Strategic Analysis of Financial Markets,' — Framework, is premised on the belief that markets can be understood only by dropping the assumptions of rationality and efficient markets in their extreme forms, and showing that markets still have an inherent order and inherent logic. But that order results primarily from the 'predictable irrationality' of investors, as well as from people's uncoordinated attempts to profit. The market patterns that result do not rely on rationality or efficiency.A framework is developed for understanding financial markets using a combination of psychology, statistics, game and gambling analysis, market history and the author's experience. It expresses analytically how professional investors and traders think about markets — as games in which other participants employ inferior, partially predictable strategies. Those strategies' interactions can be toxic and lead to booms, bubbles, busts and crashes, or can be less dramatic, leading to various patterns that are mistakenly called 'market inefficiencies' and 'stylized facts.'A logical case is constructed, starting from two foundations, the psychology of human decision making and the 'Fundamental Laws of Gambling.' Applying the Fundamental Laws to trading leads to the idea of 'gambling rationality' (grationality), replacing the efficient market's concept of 'rationality.' By classifying things that are likely to have semi-predictable price impacts (price 'distorters'), one can identify, explore through data analysis, and create winning trading ideas and systems. A structured way of doing all this is proposed: the six-step 'Strategic Analysis of Market Method.' Examples are given in this and Volume 2.Volume 2 of 'The Strategic Analysis of Financial Markets' — Trading System Analytics, continues the development of Volume 1 by introducing tools and techniques for developing trading systems and by illustrating them using real markets. The difference between these two Volumes and the rest of the literature is its rigor. It describes trading as a form of gambling that when properly executed, is quite logical, and is well known to professional gamblers and analytical traders.But even those elites might be surprised at the extent to which quantitative methods have been justified and applied, including a life cycle theory of trading systems. Apart from a few sections that develop background material, Volume 2 creates from scratch a trading system for Eurodollar futures using principles of the Strategic Analysis of Markets Method (SAMM), a principled, step-by-step approach to developing profitable trading systems. It has an entire Chapter on mechanical methods for testing and improvement of trading systems, which transcends the rather unstructured and unsatisfactory 'backtesting' literature. It presents a breakout trend following system developed using factor models. It also presents a specific pairs trading system, and discusses its life cycle from an early, highly profitable period to its eventual demise. Recent developments in momentum trading and suggestions on improvements are also discussed.
This volume contains papers which were presented at the XV Latin American Congress of Probability and Mathematical Statistics (CLAPEM) in December 2019 in Mérida-Yucatán, México. They represent well the wide set of topics on probability and statistics that was covered at this congress, and their high quality and variety illustrates the rich academic program of the conference.
In today’s digital transformation environments, a rigorous cybersecurity approach to effective risk management — including contingency planning, outlining immediate actions, preparing post-breach responses — is central to defending organizations’ interconnected computer systems, networks, and infrastructure resources from malicious cyber-attacks. Specifically, cybersecurity technologies, processes, and practices need to be generalized and applied to intrusion detection and prevention measures. This entails analyzing profiles of cyber-attackers and building cyber-attack models for behavior simulation that can effectively counter such attacks. This comprehensive volume aims to cover all essential aspects of cybersecurity in digital transformation and to provide a framework for considering the many objectives and requirements involved. In addition to introducing theoretical foundations, the work also offers practical techniques for defending against malicious cybercriminals. Topics and features: Explores cybersecurity’s impact on the dynamics of interconnected, complex cyber- and physical systems, infrastructure resources, and networks Provides numerous examples of applications and best practices Considers methods that organizations can use to assess their cybersecurity awareness and/or strategy Describes anomaly intrusion detection, a key tool in thwarting both malware and theft (whether by insiders or external parties) of corporate data Addresses cyber-attacker profiles, cyber-attack models and simulation, cybersecurity ontology, access-control mechanisms, and policies for handling ransomware attacks Discusses the NIST Cybersecurity Framework, MITRE Adversarial Tactics, Techniques and Common Knowledge, CIS Critical Security Controls, and the ISA/IEC 62442 Cybersecurity Standard Gathering all the relevant information, this practical guide is eminently suitable as a self-study resource for engineers, scientists, computer scientists, and chief information officers. Further, with its many examples of best practices, it can serve as an excellent text for graduate-level courses and research into cybersecurity. Dietmar P. F. Möller, a retired full professor, is affiliated with the Institute for Mathematics at Clausthal University of Technology, Germany. He was an author of several other Springer titles, including Guide to Automotive Connectivity and Cybersecurity.
This book provides information on advanced communication technology used in Industry 4.0 and 5.0. The book covers a variety of technologies such as signal processing, system designing, computer vision, and artificial intelligence and explains their benefits, usage, and market values in Industry 4.0 and 5.0. The authors present technological tools for industrial applications and give examples of their usage of system design, modeling, artificial intelligence, internet of things and robotics. This book covers the impact of these technologies in various industrial applications and provides future technological tools that will be helpful in future planning and development. The book is pertinent to researchers, academics, professionals, planners, and student’s interest in Industry 5.0.
