This dynamic reference work provides solutions to vital algorithmic problems for scholars, researchers, practitioners, teachers and students in fields such as computer science, mathematics, statistics, biology, economics, financial software, and medical informatics.
This second edition is broadly expanded, building upon the success of its former edition with more than 450 new and updated entries. These entries are designed to ensure algorithms are presented from growing areas of research such as bioinformatics, combinatorial group testing, differential privacy, enumeration algorithms, game theory, massive data algorithms, modern learning theory, social networks, and VLSI CAD algorithms.
Over 630 entries are organized alphabetically by problem, with subentries allowing for distinct solutions. Each entry includes a description of the basic algorithmic problem; the input and output specifications; key results; examples of applications; citations to key literature, open problems, experimental results, links to data sets and downloadable code.
All entries are peer-reviewed, written by leading experts in the field—and each entry contains links to a summary of the author’s research work.
This defining reference is available in both print and online—a dynamic living work with hyperlinks to related entries, cross references citations, and a myriad other valuable URLs.
New and Updated entries include:
Algorithmic Aspects of Distributed Sensor Networks,
Algorithms for Modern Computers
Bioinformatics
Certified Reconstruction and Mesh Generation
Combinatorial Group Testing
Compression of Text and Data Structures
Computational Counting
Computational Economics
Computational Geometry
Differential Privacy
Enumeration Algorithms
Exact Exponential Algorithms
Game Theory
Graph Drawing
Group Testing
Internet Algorithms
Kernels and Compressions
Massive Data Algorithms
Mathematical Optimization
Modern Learning Theory
Social Networks
Stable Marriage Problems, k-SAT Algorithms
Sublinear Algorithms
Tile Self-Assembly
VLSI CAD Algorithms
Ming-Yang Kao is Professor of Computer Science at the Northwestern University, Evanston. He got a B.S. in Mathematics, 1978 at the National Taiwan University, Republic of China (Taiwan) and his Ph.D. in Computer Science, 1986, at Yale University, USA.
Prof. Kao studies the design, analysis and implementation of algorithms. His work spans a broad range of applications including bioinformatics, computational finance, electronic commerce, and nanotechnology. Kao's most recent research includes work on DNA self-assembly, variants of the traveling salesman problem, and graph labeling problems.
Kao heads the EECS Computing, Algorithms & Applications Division and is the editor-in-chief of Algorithmica.
