The text covers important algorithm design techniques, like greedy algorithms, dynamic programming, 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 emphasises the role of randomization in algorithm design, and gives numerous applications ranging from data-structures like skip-lists to dimensionality reduction methods.

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