Course Notes - CS 260P - Fundamentals of Algorithms with Applications
The following documents outline the notes for the course CS 260P.
Note: All the notes are in PDF format.
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Notes by Lecture Schedule
- 1:
Introduction. Growth of functions.
Basic data structures.
Reading: Goodrich-Tamassia, Chapters 1-7, with emphasis on Chapter 1.
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2:
Sorting and Selection.
Reading: Goodrich-Tamassia, Chapters 8-9.
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3:
Fundamental techniques.
The greedy method.
Divide-and-conquer.
Reading: Goodrich-Tamassia, Chapters 10-11.
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4:
Dynamic programming.
Reading: Goodrich-Tamassia, Chapter 12.
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5:
Dynamic programming and Graphs.
Reading: Goodrich-Tamassia, Chapter 13.
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6:
Graph algorithms.
Reading: Goodrich-Tamassia, Chapters 13-14.
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7:
More graph algorithms.
Reading: Goodrich-Tamassia, Chapters 15-16.
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8:
NP-Completeness.
Reading: Goodrich-Tamassia, Chapter 17.
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9:
More NP-completeness and
approximation algorithms.
Reading: Goodrich-Tamassia, Chapters 17-18.
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10:
Randomized Algorithms and
the Stable Marriage Problem.
Reading: Goodrich-Tamassia, Chapter 19.
Michael T. Goodrich
Department of Computer Science
University of California, Irvine, CA 92697-3435 USA