randomized algorithms
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- 6 5220 Lecture 4 Game theory, Lower Bounds 1, Coupon Collecting, Stable Matching.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 3 Adelman's theorem, Game tree evaluationMIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 2 Min-cut, Complexity theory.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 1 Introduction to Randomized Algorithms. Quicksort, BSP.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 16: Parallel Maximal Independent Set. Derandomization.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 18 Sampling: transitive closure. DNF counting, rare events.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 14: Symmetry breaking. Parallel Algorithms. Ethernet. Perfect matching.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 13: Fingerprinting by polynomials, perfect matching, network coding.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 12: Text search. Bloom filters.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 11: Consistent Hashing. Fingerprinting.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 10: 2 Choices (cont). Cuckoo Hashing.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 8: The power of two choices.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 7: Chernoff Bound. Randomized routing.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6 5220 Lecture 6 Median finding. Pseudorandom numbers.MIT 6.5220 Randomized Algorithms Fall 2025Notes
- 6.5220 Lecture 5 Deviations: Markov, Chebyshev. Balls in BinsMIT 6.5220 Randomized Algorithms Fall 2025Notes
- Lovász Local lemma (Randomized algorithms, Fall 2022, Lecture 15)Randomized Algorithms, Fall 2022Notes
- PAC learning (Randomized algorithms, Fall 2022, Lecture 13)Randomized Algorithms, Fall 2022Notes
- Entropy and codes (Randomized algorithms, Fall 2022, Lecture 14)Randomized Algorithms, Fall 2022Notes
- Geometric sampling (Randomized algorithms, Fall 2022, Lecture 12)Randomized Algorithms, Fall 2022Notes
- Randomized tree metrics (Randomized algorithms, Fall 2022, Lecture 11)Randomized Algorithms, Fall 2022Notes
- Sparsest cut (Randomized algorithms, Fall 2022, Lecture 10)Randomized Algorithms, Fall 2022Notes
- Locality-sensitive hashing (Randomized algorithms, Fall 2022, Lecture 9)Randomized Algorithms, Fall 2022Notes
- Dimensionality reduction (Randomized algorithms, Fall 2022, Lecture 8)Randomized Algorithms, Fall 2022Notes
- Distinct elements (Randomized algorithms, Fall 2022, Lecture 7)Randomized Algorithms, Fall 2022Notes
- Randomized rounding (Randomized algorithms, Fall 2022, Lecture 6)Randomized Algorithms, Fall 2022Notes
- Random sums and graphs (Randomized algorithms, Fall 2022, Lecture 5)Randomized Algorithms, Fall 2022Notes
- Randomized minimum cut (Randomized algorithms, Fall 2022, Lecture 4)Randomized Algorithms, Fall 2022Notes
- Hash tables and linear probing (Randomized algorithms, Fall 2022, Lecture 3)Randomized Algorithms, Fall 2022Notes
- Hashing and heavy hitters (Randomized algorithms, Fall 2022, Lecture 2)Randomized Algorithms, Fall 2022Notes
- Randomized searching and sorting (Randomized algorithms, Fall 2022, Lecture 1)Randomized Algorithms, Fall 2022Notes
- CSE290A, Spring 2020: Lec 16, the Count-Min sketch, and the AMS algorithm for frequency momentsCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 15, improved distinct elements and introduction to heavy hittersCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 14, counting distinct elements in the streaming modelCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 12, Introduction to distribution testingCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 11, the Poisson approximating and PoissonlzationCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 9, proof of the Chernoff upper tail, discussion of the tail boundCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: The Johnson-Lindenstrauss lemmaCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Estimating the average degree of a graphCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 7, Walker's alias methodCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Randomized Algorithms: Lec6, Cohen-Lewis matrix multiplicationCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 5, improved Karp-Luby-MadrasCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A Spring 2020: Lec 4, Karp-Luby importance samplingCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 3, Chernoff boundsCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020: Lec 2, the Hoeffing boundCSE290A, Spring 2020: Randomized AlgorithmsNotes
- CSE290A, Spring 2020, Lec1: Quicksort and Karger's mincutCSE290A, Spring 2020: Randomized AlgorithmsNotes
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