algorithms lecture

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1. 1▶Distributed Algorithms 2020: lecture 11a · Hardness of coloringDistributed Algorithms 2020Notes
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2. 2▶Distributed Algorithms 2020: lecture 10a · Sinkless orientationDistributed Algorithms 2020Notes
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3. 3▶Distributed Algorithms 2020: lecture 9a · Round eliminationDistributed Algorithms 2020Notes
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4. 4▶Distributed Algorithms 2020: lecture 8a · LocalityDistributed Algorithms 2020Notes
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5. 5▶Distributed Algorithms 2020: lecture 7a · Covering mapsDistributed Algorithms 2020Notes
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6. 6▶Distributed Algorithms 2020: lecture 6a · Randomized coloringDistributed Algorithms 2020Notes
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7. 7▶Distributed Algorithms 2020: lecture 5a · APSPDistributed Algorithms 2020Notes
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8. 8▶Distributed Algorithms 2020: lecture 4a · Graph coloringDistributed Algorithms 2020Notes
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9. 9▶Distributed Algorithms 2020: lecture 3a · PN modelDistributed Algorithms 2020Notes
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10. 10▶Distributed Algorithms 2020: lecture 2a · Graph theoryDistributed Algorithms 2020Notes
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11. 11▶Distributed Algorithms 2020: lecture 1b · Coloring cyclesDistributed Algorithms 2020Notes
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12. 12▶Distributed Algorithms 2020: lecture 1a · IntroductionDistributed Algorithms 2020Notes
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13. 13▶Advanced Algorithms - Lecture 15 (Fall 2016)Advanced Algorithms (Fall 2016)Notes
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14. 14▶Advanced Algorithms - Lecture 14 (Fall 2016)Advanced Algorithms (Fall 2016)Notes
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15. 15▶Advanced Algorithms - Lecture 13 (Fall 2016)Advanced Algorithms (Fall 2016)Notes
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16. 16▶Advanced Algorithms Lecture 12Advanced Algorithms (Fall 2016)Notes
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17. 17▶Advanced Algorithm Lecture 11Advanced Algorithms (Fall 2016)Notes
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18. 18▶Advanced Algorithms Lecture 10Advanced Algorithms (Fall 2016)Notes
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19. 19▶Advanced Algorithms Lecture 9Advanced Algorithms (Fall 2016)Notes
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20. 20▶Advanced Algorithms Lecture 8Advanced Algorithms (Fall 2016)Notes
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21. 21▶Advanced Algorithms Lecture 7Advanced Algorithms (Fall 2016)Notes
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22. 22▶Advanced Algorithms Lecture 6Advanced Algorithms (Fall 2016)Notes
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23. 23▶Advanced Algorithms Lecture 5Advanced Algorithms (Fall 2016)Notes
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24. 24▶Advanced Algorithms Lecture 4Advanced Algorithms (Fall 2016)Notes
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25. 25▶Advanced Algorithms Lecture 3Advanced Algorithms (Fall 2016)Notes
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26. 26▶Advanced Algorithms Lecture 2Advanced Algorithms (Fall 2016)Notes
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27. 27▶Advanced Algorithms Lecture 1Advanced Algorithms (Fall 2016)Notes
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28. 28▶A Second Course in Algorithms (Lecture 15: Introduction to Approximation Algorithms)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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29. 29▶A Second Course in Algorithms (Lecture 14: Online Bipartite Matching)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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30. 30▶A Second Course in Algorithms (Lecture 13: Online Scheduling and Online Steiner Tree)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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31. 31▶A Second Course in Algorithms (Lecture 12: Applications of Multiplicative Weights to Games and LPs)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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32. 32▶A Second Course in Algorithms (Lecture 11: Online Learning and the Multiplicative Weights Algorithm)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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33. 33▶A Second Course in Algorithms (Lecture 10: The Minimax Theorem & Algorithms for Linear Programming)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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34. 34▶A Second Course in Algorithms (Lecture 9: Linear Programming Duality --- Part 2)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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35. 35▶A Second Course in Algorirthms (Lecture 8: Linear Programming Duality --- Part 1)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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36. 36▶A Second Course in Algorithms (Lecture 7: Linear Programming: Introduction and Applications)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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37. 37▶A Second Course in Algorithms (Lecture 6: Generalizations of Maximum Flow and Bipartite Matching)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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38. 38▶A Second Course in Algorithms (Lecture 5: Minimum-Cost Bipartite Matching)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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39. 39▶A Second Course in Algorithms (Lecture 4: Applications of Maximum Flows and Minimum Cuts)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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40. 40▶A Second Course in Algorithms (Lecture 3: The Push-Relabel Algorithm for Maximum Flow)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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41. 41▶A Second Course in Algorithms (Lecture 2: Augmenting Path Algorithms for Maximum Flow)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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42. 42▶A Second Course in Algorithms (Lecture 1: Course Goals and Introduction to Maximum Flow)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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