BPP (complexity) and Sipser–Lautemann theorem

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between BPP (complexity) and Sipser–Lautemann theorem

BPP (complexity) vs. Sipser–Lautemann theorem

In computational complexity theory, BPP, which stands for bounded-error probabilistic polynomial time is the class of decision problems solvable by a probabilistic Turing machine in polynomial time with an error probability bounded away from 1/2 for all instances. In computational complexity theory, the Sipser–Lautemann theorem or Sipser–Gács–Lautemann theorem states that bounded-error probabilistic polynomial (BPP) time is contained in the polynomial time hierarchy, and more specifically Σ2 ∩ Π2.

Similarities between BPP (complexity) and Sipser–Lautemann theorem

BPP (complexity) and Sipser–Lautemann theorem have 5 things in common (in Unionpedia): Arthur–Merlin protocol, Complement (complexity), Computational complexity theory, Michael Sipser, Polynomial hierarchy.

Arthur–Merlin protocol

In computational complexity theory, an Arthur–Merlin protocol is an interactive proof system in which the verifier's coin tosses are constrained to be public (i.e. known to the prover too).

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Complement (complexity)

In computational complexity theory, the complement of a decision problem is the decision problem resulting from reversing the yes and no answers.

BPP (complexity) and Complement (complexity) · Complement (complexity) and Sipser–Lautemann theorem · See more »

Computational complexity theory

Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.

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Michael Sipser

Michael Fredric Sipser (born September 17, 1954) is a theoretical computer scientist who has made early contributions to computational complexity theory.

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Polynomial hierarchy

In computational complexity theory, the polynomial hierarchy (sometimes called the polynomial-time hierarchy) is a hierarchy of complexity classes that generalize the classes P, NP and co-NP to oracle machines.

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The list above answers the following questions

What BPP (complexity) and Sipser–Lautemann theorem have in common
What are the similarities between BPP (complexity) and Sipser–Lautemann theorem

BPP (complexity) and Sipser–Lautemann theorem Comparison

BPP (complexity) has 52 relations, while Sipser–Lautemann theorem has 9. As they have in common 5, the Jaccard index is 8.20% = 5 / (52 + 9).

References

This article shows the relationship between BPP (complexity) and Sipser–Lautemann theorem. To access each article from which the information was extracted, please visit:

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