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Theory of Computation: Conclusions and Complexity Theory
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Related lectures (37)
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Elements of Computational Complexity
Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.
P vs NP: Complexity Theory
Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.
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Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.
Theory of Computation: NP Complexity
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Complexity Classes: Introduction and Examples
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Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.
Complexity of Algorithms: Big-O Notation
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Theory of Computation: Monotone Complexity and XOR-SAT Lower Bounds
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Computational Complexity: Theory and Applications
Explores computational complexity, NP-completeness, and polynomial reductions in theoretical computer science.
Understanding Complexity: Algorithms and NP Problems
Covers complexity classes, tractable problems, the class NP, NP-complete problems, and summarizes the concept of tractable problems.
Understanding Complexity: Tractable Problems and NP-Complete
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Cryptanalysis: Public-Key & The Power of Interaction
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Theory of Computation: Complexity of Problems
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Berni Alder Prize: Celebrating 50 Years of CECAM
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Elements of computational complexity
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Covers classical and quantum computational complexity concepts and implications.
Theory of Computation: Decidability and Complexity
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Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.
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