Thursday, April 11, 2019

Algorithms (Free PDF)

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This book evolved over the past ten years from a set of lecture notes developed while teaching the undergraduate Algorithms course at Berkeley and U.C. San Diego. Our way of teaching this course evolved tremendously over these years in a number of directions, partly to address our students' background (undeveloped formal skills outside of programming), and partly to re ect the maturing of the eld in general, as we have come to see it. The notes increasingly crystallized into a narrative, and we progressively structured the course to emphasize the “story line” implicit in the progression of the material. As a result, the topics were carefully selected and clustered. No attempt was made to be encyclopedic, and this freed us to include topics traditionally de-emphasized or omitted from most Algorithms books.

Playing on the strengths of our students (shared by most of today's undergraduates in Computer Science), instead of dwelling on formal proofs we distilled in each case the crisp mathematical idea that makes the algorithm work. In other words, we emphasized rigor over formalism. We found that our students were much more receptive to mathematical rigor of this form. It is this progression of crisp ideas that helps weave the story.

0. Prologue
1. Algorithms with numbers
Randomized algorithms: a virtual chapter
2. Divide-and-conquer algorithms
3. Decompositions of graphs
4. Paths in graphs
5. Greedy algorithms
6. Dynamic programming
7. Linear programming and reductions
8. NP-complete problems
9. Coping with NP-completeness
10. Quantum algorithms
Historical notes and further reading

Author Details
"S. Dasgupta"

"C. H. Papadimitriou"

"U. V. Vazirani"

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