高级算法 (Fall 2023) / Course materials: Difference between revisions

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:'''''Lx = b: laplacian solvers and their algorithmic applications'''''.
:'''''Lx = b: laplacian solvers and their algorithmic applications'''''.
:Foundations and Trends® in Theoretical Computer Science, 2012.
:Foundations and Trends® in Theoretical Computer Science, 2012.
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:Lap Chi Lau.
:'''''Eigenvalues and Polynomials'''''.
:https://cs.uwaterloo.ca/~lapchi/cs860/notes/eigenpoly.pdf
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Revision as of 03:55, 12 September 2023

Course textbooks

Rajeev Motwani and Prabhakar Raghavan.
Randomized Algorithms.
Cambridge University Press, 1995.
Vijay Vazirani.
Approximation Algorithms.
Springer-Verlag, 2001.

References and further readings

Michael Mitzenmacher and Eli Upfal.
Probability and Computing: Randomized Algorithms and Probabilistic Analysis.
Cambridge University Press, 2005.
Noga Alon and Joel Spencer.
The Probabilistic Method, 4th edition.
Wiley, 2016.
David P. Williamson and David Shmoys.
The Design of Approximation Algorithms.
Cambridge University Press, 2011.
Bernhard Korte and Jens Vygen.
Combinatorial Optimization: theory and algorithms, 3rd edition.
Springer, 2008.
Nisheeth K. Vishnoi.
Lx = b: laplacian solvers and their algorithmic applications.
Foundations and Trends® in Theoretical Computer Science, 2012.
Lap Chi Lau.
Eigenvalues and Polynomials.
https://cs.uwaterloo.ca/~lapchi/cs860/notes/eigenpoly.pdf
Sanjoy Dasgupta, Christos Papadimitriou and Umesh Vazirani.
Algorithms.
McGraw-Hill, 2006.