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Davidmanheim comments on The Best Textbooks on Every Subject - Less Wrong

167 Post author: lukeprog 16 January 2011 08:30AM

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Comment author: Davidmanheim 18 January 2011 03:38:52PM 0 points [-]

As a counterpoint to Hopcroft+Ullman, from another who has not read other books, Problem Solving in Automata, Languages, and Complexity by Ding-Zhu Du and Ker-I Ko was terrific. I did it as an undergraduate independent study class, completely from this book, and found it to be easy to follow if you are willing to work through problems.

Maybe we need someone who knows something more on the subject?

Comment author: Jonathan_Graehl 26 January 2011 02:47:37AM 0 points [-]

Hopcroft+Ullman is very proof oriented. Sometimes the proof is constructive (by giving an algorithm and proving its correctness). I liked it. There may be much better available for self-study.

Specialty algorithms: I briefly referenced Numerical Optimization and it seems better than Numerical Recipes in C. I didn't read it cover to cover.

Algorithms on Strings, Trees, and Sequences (Gusfield) was definitely a good source for computational biology algorithms (I don't do computation biology, but it explains fairly well things like suffix trees and their applications, and algorithms matching a set of patterns against substrings of running text).

Foundations of Natural Language Processing is solid. I don't think there's a better textbook (for the types of dumb, statistics/machine-learning based, analysis of human speech/text that are widely practiced). It's better than "Natural Language Understanding" (Allen), which is more old-school-AI.