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Sum of Squares: Theory and Applications
This volume is based on lectures delivered at the 2019 AMS Short Course “Sum of Squares: Theory and Applications”, held January 14–15, 2019, in Baltimore, Maryland. This book provides a concise state-of-the-art overview of the theory and applications of polynomials that are sums of squares. This is an exciting and timely topic, with rich connections to many areas of mathematics, including polynomial and semidefinite optimization, real and convex algebraic geometry, and theoretical computer science. The six chapters introduce and survey recent developments in this area; specific topics include the algebraic and geometric aspects of sums of squares and spectrahedra, lifted representations of convex sets, and the algorithmic and computational implications of viewing sums of squares as a meta algorithm. The book also showcases practical applications of the techniques across a variety of areas, including control theory, statistics, finance and machine learning.
Hybrid Systems: Computation and Control
This book constitutes the refereed proceedings of the 7th International Workshop on Hybrid Systems: Computation and Control, HSCC 2004, held in Philadelphia, PA, USA, in March 2004. The 43 revised full papers presented together with an invited article were carefully reviewed and selected from 117 submissions. The papers address all current issues in hybrid systems such as tools for analysis and verification, control and optimization, modeling and engineering applications, and emerging topics in programming language support and implementation; a special focus is on the interplay between biomolecular networks, systems biology, formal methods, and control of hybrid systems.
Interpreting Godel
In this groundbreaking volume, leading philosophers and mathematicians explore Kurt Gödel's work on the foundations and philosophy of mathematics.
Mastering Spark for Data Science
Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products About This Book Develop and apply advanced analytical techniques with Spark Learn how to tell a compelling story with data science using Spark's ecosystem Explore data at scale and work with cutting edge data science methods Who This Book Is For This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and pop...
Recommender Systems
Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business and are used in a wide variety of industries, ranging from entertainment and social networking to information technology, tourism, education, agriculture, healthcare, manufacturing, and retail. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how this theory is applied and implemented in actual systems. The book examines several classes of recommendation algorithms, including Machine learning algorithms Community detection algorithms Filtering algorithms Various efficient and robust product recommender s...
Automata, Languages and Programming
The refereed proceedings of the 30th International Colloquium on Automata, Languages and Programming, ICALP 2003, held in Eindhoven, The Netherlands in June/July 2003. The 84 revised full papers presented together with six invited papers were carefully reviewed and selected from 212 submissions. The papers are organized in topical sections on algorithms, process algebra, approximation algorithms, languages and programming, complexity, data structures, graph algorithms, automata, optimization and games, graphs and bisimulation, online problems, verification, the Internet, temporal logic and model checking, graph problems, logic and lambda-calculus, data structures and algorithms, types and categories, probabilistic systems, sampling and randomness, scheduling, and geometric problems.
Survey of Text Mining
Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
Mathematical Reviews
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