Rajeev Motwani

Jeffrey D. Ullman

John E. Hopcroft

This classic book on formal languages, automata theory, and computational complexity has been updated to present theoretical concepts in a concise and straightforward manner with the increase of hands-on, practical applications. This new edition comes with Gradiance, an online assessment tool developed for computer science. Please note, Gradiance is no longer available with this book, as we no longer support this product.

Pearson New International Edition

Introduction to Automata Theory, Languages, and Computation

Alfred V. Aho

The Design and Analysis of Computer Algorithms

John Hopcroft

fred V. Aho

Ullman D. Jeffrey

Data Structures and Algorithms

It has been more than 20 years since this classic book on formal languages, automata theory, and computational complexity was first published. With this long-awaited revision, the authors continue to present the theory in a concise and straightforward manner, now with an eye out for the practical applications. They have revised this book to make it more accessible to today's students, including the addition of more material on writing proofs, more figures and pictures to convey ideas, side-boxes to highlight other interesting material, and a less formal writing style. Exercises at the end of each chapter, including some new, easier exercises, help readers confirm and enhance their understanding of the material. *NEW! Completely rewritten to be less formal, providing more accessibility to todays students. *NEW! Increased usage of figures and pictures to help convey ideas. *NEW! More detail and intuition provided for definitions and proofs. *NEW! Provides special side-boxes to present supplemental material that may be of interest to readers. *NEW! Includes more exercises, including many at a lower level. *NEW! Presents program-like notation for PDAs and Turing machines. *NEW! Increas

Xiaotie Deng

Jinyun Xue

This book constitutes the refereed proceedings of the Third International Frontiers of Algorithmics Workshop, FAW 2009, held in Hefei, Anhui, China, in June 2009. The 33 revised full papers presented together with the abstracts of 3 invited talks were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on graph algorithms; game theory with applications; graph theory, computational geometry; machine learning; parameterized algorithms, heuristics and analysis; approximation algorithms; as well as pattern recognition algorithms, large scale data mining.

Third International Workshop, FAW 2009, Hefei, China, June 20-23, 2009, Proceedings

Frontiers in Algorithmics

Avrim Blum

Ravindran Kannan

"This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"--

Foundations of Data Science

Automi, linguaggi e calcolabilità

John E. Hopcroft

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