Design and Analysis of Algorithms

The text covers important algorithm design techniques, such as greedy algorithms, dynamic programming, and divide-and-conquer, and gives applications to contemporary problems. Techniques including Fast Fourier transform, KMP algorithm for string matching, CYK algorithm for context free parsing and gradient descent for convex function minimization are discussed in detail. The book's emphasis is on computational models and their effect on algorithm design. It gives insights into algorithm design techniques in parallel, streaming and memory hierarchy computational models. The book also emphasizes the role of randomization in algorithm design, and gives numerous applications ranging from data-structures such as skip-lists to dimensionality reduction methods.

• Discusses important concepts including graph algorithms, parallel algorithms and approximation algorithms that are explained in detail
• Emphasizes alternate and realistic computational frameworks including parallel, memory hierarchy and streaming
• Covers new models of computation including string matching, streaming algorithms and geometric algorithms
• Real-life applications and numerical problems are spread throughout the text for the benefit of the reader