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min cost

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  1. CSE202, Lec 15: The Calinescu-Karloff-Rabani relaxation for multiway cut, and the 3/2-approximationCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  2. CSE202, Lec 14: Introduction to multiway cut and 2-approximationsCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  3. CSE202, Lec 13: Rounding of LPs, integrality gaps, and an analysis of set coverCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  4. CSE202, Lec 12: Integrality of polyhedra, totally unimodular matricesCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  5. CSE202, Lec 11: More on the ellipsoid algorithmCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  6. CSE202, Lec 10: Solving LPsCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  7. CSE202, Lec 9: The Hungarian algorithm for min weight perfect bipartite matchingCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  8. CSE202, Lec 8: Primal dual algorithms for mincost flowCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  9. CSE202, Lec 7: A deeper look at min cost flowCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  10. CSE202, Lec 6: Proof of the max-flow-mincut theorem, introduction to Min cost flowCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  11. CSE 202, Lec 5: LP dualityCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  12. CSE202, Lec 4: Linear programmingCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  13. CSE 202, Lec 3: Max flow and the Edmonds-Karp algorithmCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  14. CSE202, Lec 2: Edmond's blossom algorithmCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  15. CSE202, Lec 1: Bipartite matchingCSE202, Spring 2021: Combinatorial AlgorithmsNotes
  16. MIT 6.854 Spring 2016 Lecture 16: Interior Point MethodsMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  17. MIT 6.854 Spring 2016 Lecture 15: Gradient DescentMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  18. MIT 6.854 Spring 2016 Lecture 14: Rounding Linear Programming RelaxationsMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  19. MIT 6.854 Spring 2016 Lecture 8: Capacity Scaling and Min Cost MatchingMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  20. MIT 6.854 Spring 2016 Lecture 13: Submodular FunctionsMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  21. MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid MethodMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  22. MIT 6.854 Spring 2016 Lecture 10: Introduction to Linear ProgrammingMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  23. MIT 6.854 Spring 2016 Lecture 11: Strong Duality, Zero Sum Games and Complementary SlacknessMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  24. MIT 6.854 Spring 2016 Lecture 9: Min Cost Flow, Goldberg-TarjanMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  25. MIT 6.854 Spring 2016 Lecture 7: Flow Decomposition and Augmenting PathsMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  26. MIT 6.854 Spring 2016 Lecture 6: Nearest Neighbor Search and LSHMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  27. MIT 6.854 Spring 2016 Lecture 3 part 2MIT 6.854 (Advanced Algorithms), Spring 2016Notes
  28. MIT 6.854 Spring 2016 Lecture 5: Johnson Lindenstrauss Lemma and ExtensionsMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  29. MIT 6.854 Spring 2016 Lecture 4: Distinct Elements and Heavy HittersMIT 6.854 (Advanced Algorithms), Spring 2016Notes
  30. MIT 6.854 Spring 2016 Lecture 3: Consistent Hashing and Random TreesMIT 6.854 (Advanced Algorithms), Spring 2016Notes

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