spring lec

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1. 1▶CSE290A, Spring 2020: Lec 16, the Count-Min sketch, and the AMS algorithm for frequency momentsCSE290A, Spring 2020: Randomized AlgorithmsNotes
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2. 2▶CSE290A, Spring 2020: Lec 15, improved distinct elements and introduction to heavy hittersCSE290A, Spring 2020: Randomized AlgorithmsNotes
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3. 3▶CSE290A, Spring 2020: Lec 14, counting distinct elements in the streaming modelCSE290A, Spring 2020: Randomized AlgorithmsNotes
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4. 4▶CSE290A, Spring 2020: Lec 12, Introduction to distribution testingCSE290A, Spring 2020: Randomized AlgorithmsNotes
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5. 5▶CSE290A, Spring 2020: Lec 11, the Poisson approximating and PoissonlzationCSE290A, Spring 2020: Randomized AlgorithmsNotes
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6. 6▶CSE290A, Spring 2020: Lec 9, proof of the Chernoff upper tail, discussion of the tail boundCSE290A, Spring 2020: Randomized AlgorithmsNotes
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7. 7▶CSE290A, Spring 2020: The Johnson-Lindenstrauss lemmaCSE290A, Spring 2020: Randomized AlgorithmsNotes
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8. 8▶CSE290A, Spring 2020: Estimating the average degree of a graphCSE290A, Spring 2020: Randomized AlgorithmsNotes
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9. 9▶CSE290A, Spring 2020: Lec 7, Walker's alias methodCSE290A, Spring 2020: Randomized AlgorithmsNotes
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10. 10▶CSE290A, Randomized Algorithms: Lec6, Cohen-Lewis matrix multiplicationCSE290A, Spring 2020: Randomized AlgorithmsNotes
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11. 11▶CSE290A, Spring 2020: Lec 5, improved Karp-Luby-MadrasCSE290A, Spring 2020: Randomized AlgorithmsNotes
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12. 12▶CSE290A Spring 2020: Lec 4, Karp-Luby importance samplingCSE290A, Spring 2020: Randomized AlgorithmsNotes
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13. 13▶CSE290A, Spring 2020: Lec 3, Chernoff boundsCSE290A, Spring 2020: Randomized AlgorithmsNotes
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14. 14▶CSE290A, Spring 2020: Lec 2, the Hoeffing boundCSE290A, Spring 2020: Randomized AlgorithmsNotes
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15. 15▶CSE290A, Spring 2020, Lec1: Quicksort and Karger's mincutCSE290A, Spring 2020: Randomized AlgorithmsNotes
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