Lecture notes
Notes will usually be posted the day before lecture.
Lecture 1 (Jan 20): Introduction [pdf] [one]
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Lecture 2 (Jan 22): Tail inequalities [pdf] [one]
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Lecture 3 (Jan 27): Balls and bins [pdf] [one]
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Lecture 4 (Jan 29): Hashing [pdf] [one]
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Lecture 5 (Feb 3): Data streaming [pdf] [one]
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Lecture 6 (Feb 5): no new notes
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Lecture 7 (Feb 10): Polynomial identity testing [pdf] [one]
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Lecture 8 (Feb 12): Network coding [pdf] [one]
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Lecture 9 (Feb 17): Probabilistic methods [pdf] [one]
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Lecture 10 (Feb 19): Local lemma [pdf] [one]
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Lecture 11 (Feb 24): Random walks [pdf] [one]
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Lecture 12 (Feb 26): Linear programming [pdf] [one]
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Lecture 13 (Mar 3): Matching polytopes [pdf] [one]
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Lecture 14 (Mar 5): Spanning tree polytopes [pdf] [one]
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Lecture 15 (Mar 10): LP duality [pdf] [one]
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Lecture 16 (Mar 12): no new notes
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Lecture 17 (Mar 17): Multiplicative update method [pdf] [one]
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Lecture 18 (Mar 19): Semidefinite
programming [pdf] [one](updated)
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Lecture 19 (Mar 31): SDP duality [pdf] [one]
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Lecture 20 (Apr 2): Matrix multiplicative update [pdf] [one]
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Lecture 21 (Apr 7): Spectral graph theory [pdf] [one]
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Lecture 22 (Apr 9): Cheeger's inequality [pdf] [one]
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Lecture 23 (Apr 14): Mixing time [pdf] [one]
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Lecture 24 (Apr 16): Small-set expansion [pdf] [one]
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Lecture 25 (Apr 21): Electrical networks [pdf] [one]
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Lecture 26 (Apr 23): Spectral sparsification [pdf] [one]
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Lecture 27 (Apr 28): Laplacian solver [pdf] [one]
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Lecture 28 (Apr 30): Maximum flow [pdf] [one]
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