Computer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the
The Third International Frontiers of Algorithmics Workshop (FAW 2009), held during June 20–23,2009 at Hefei University of Technology, Hefei, Anhui, China, continued to provide a focused forum on curre
This book constitutes the refereed proceedings of the 6th International Frontiers of Algorithmics Workshop, FAW 2012, and the 8th International Conference on Algorithmic Aspects in Information and Man
The subject is at the crossroads of Discrete Mathematics and Computer Science, with a strong probabilistic flavor. The main tools used before are on the one hand analytic (generating functions and com
There are several approaches to attack hard problems. All have their merits, but also their limitations, and need a large body of theory as their basis. A number of books for each one exist: books on
Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.
Computer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the
Matching problems with preferences are all around us — they arise when agents seek to be allocated to one another on the basis of ranked preferences over potential outcomes. Efficient algorithms are n
Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I analyze the data? To answer these questions the book draws on ideas from algorithm design and analysis, computer systems, and statistics and data analysis. The wide-ranging discussion includes a tutorial on system clocks and CPU timers, a survey of strategies for tuning algorithms and data structures, a cookbook of methods for generating random combinatorial inputs, and a demonstration of variance reduction techniques. The book can be used by anyone who has taken a course or two in data structures and algorithms. A companion website, AlgLab (www.cs.amherst.edu/alglab) contains downloadable files, programs and tools for use in experimental projects.
Providing a thorough, well-written and thoughtful study of the fundamental theoretical ideas of computing and examining how to design accurate and efficient algorithms, this book is ideal for an intro
In designing a network device, you make dozens of decisions that affect the speed with which it will perform—sometimes for better, but sometimes for worse. Network Algorithmics provides a complete, co
This book is concerned with those foundational questions inelementary algebra, calculus and geometry, that are almostalways left unanswered in undergraduate courses in thesesubjects. Among the
Juraj Hromkovic takes the reader on an elegant route through the theoretical fundamentals of computer science. The author shows that theoretical computer science is a fascinating discipline, full of s
