lecture linear programming

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1. 1▶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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2. 2▶A Second Course in Algorithms (Lecture 14: Online Bipartite Matching)A Second Course in Algorithms (Stanford CS261, Winter 2016)Notes
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3. 3▶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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4. 4▶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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5. 5▶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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6. 6▶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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7. 7▶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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8. 8▶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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9. 9▶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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10. 10▶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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11. 11▶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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12. 12▶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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13. 13▶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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14. 14▶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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15. 15▶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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16. 16▶Lecture 24 11/11: Online Algorithms: PagingKarger SkoltechNotes
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17. 17▶Lecture 22 11/04 Approximation Algorithms: Linear Programming RelaxationsKarger SkoltechNotes
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18. 18▶Lecture 21 11/01 Approximation Algorithms: RelaxationsKarger SkoltechNotes
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19. 19▶Lecture 20 10/30 Polynomial Approximation SchemesKarger SkoltechNotes
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20. 20▶Lecture 19 10/28 Approximation AlgorithmsKarger SkoltechNotes
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21. 21▶Lecture 18 10/25 Linear Programming: Interior PointKarger SkoltechNotes
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22. 22▶Lecture 17 10/23 Linear Programming: Simplex AlgorithmKarger SkoltechNotes
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23. 23▶Lecture 16 10/21 Linear Programming Duality ExamplesKarger SkoltechNotes
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24. 24▶Lecture 15 10/18 Linear Programming DualityKarger SkoltechNotes
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25. 25▶Lecture 14 10/16 Linear ProgrammingKarger SkoltechNotes
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