computational complexity

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1. 1▶CSE104, Lec 16: Introduction to circuit complexityCSE104, Fall 2020: Computational ComplexityNotes
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2. 2▶CSE104, Lec 15: More on the polynomial hierarchyCSE104, Fall 2020: Computational ComplexityNotes
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3. 3▶CSE104, Lec 14: The polynomial hierarchyCSE104, Fall 2020: Computational ComplexityNotes
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4. 4▶CSE104, Lec 13: NL = co-NL, the Immerman-Szelepcsenyi theoremCSE104, Fall 2020: Computational ComplexityNotes
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5. 5▶CSE104, Lec 11: Logspace reductions and NL-completenessCSE104, Fall 2020: Computational ComplexityNotes
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6. 6▶CSE104, Lec 12: Read-once certificates for NL, starting NL=co-NLCSE104, Fall 2020: Computational ComplexityNotes
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7. 7▶CSE104, Lec 10: QBF is PSPACE-complete, the notion of logspace reductionsCSE104, Fall 2020: Computational ComplexityNotes
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8. 8▶CSE104, Lec 9: Savitch's theorem, PSPACE = NPSPACECSE104, Fall 2020: Computational ComplexityNotes
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9. 9▶CSE104, Lec 8: EXP vs NEXP and the time hierarchy theoremCSE104, Fall 2020: Computational ComplexityNotes
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10. 10▶CSE104, Lec 7: co-NP and the factoring problemCSE104, Fall 2020: Computational ComplexityNotes
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11. 11▶CSE104, Lec 5: The proof of the Cook-Levin theorem and the NP-completeness of 3SATCSE104, Fall 2020: Computational ComplexityNotes
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12. 12▶CSE104: Lec 4, NP-completeness, the Cook-Levin TheoremCSE104, Fall 2020: Computational ComplexityNotes
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13. 13▶CSE104: Lec 3, the definitions of P and NPCSE104, Fall 2020: Computational ComplexityNotes
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14. 14▶CSE104, Lec 2: Turing machine simulationsCSE104, Fall 2020: Computational ComplexityNotes
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15. 15▶CSE104, Computational Complexity: Lec 1, Cantor's diagonalizationCSE104, Fall 2020: Computational ComplexityNotes
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