“Probabilistic computations: Toward a unified measure of complexity”

E926127

research paper scientific article

“Probabilistic computations: Toward a unified measure of complexity” is a seminal research paper by Andrew Yao that laid foundational concepts in computational complexity theory, particularly regarding the role and analysis of randomness in algorithms.

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All labels observed (3)

Label	Occurrences
Probabilistic computations	1
Probabilistic computations: Toward a unified measure of complexity	1
“Probabilistic computations: Toward a unified measure of complexity” canonical	1

How this entity was disambiguated

This entity first appeared as the object of triple T11438094 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: “Probabilistic computations: Toward a unified measure of complexity”
Context triple: [Andrew Yao, notableWork, “Probabilistic computations: Toward a unified measure of complexity”]

A. Blum complexity measures
Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
B. Computational Complexity: A Conceptual Perspective
Computational Complexity: A Conceptual Perspective is a graduate-level textbook that presents the foundations and key themes of computational complexity theory with an emphasis on conceptual understanding over technical detail.
C. Randomness and Computation
"Randomness and Computation" is Shafi Goldwasser's influential doctoral thesis that helped lay the foundations of modern complexity theory and cryptography by rigorously exploring the role of randomness in efficient computation.
D. Kolmogorov complexity
Kolmogorov complexity is a measure of the amount of information in an object, defined as the length of the shortest computer program that can produce it.
E. P, NP, and NP-Completeness: The Basics of Complexity Theory
"P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
F. None of above. chosen
G. Unsure - the case is ambiguous/there is not enough information to decide.

NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07

Target entity: “Probabilistic computations: Toward a unified measure of complexity”
Target entity description: “Probabilistic computations: Toward a unified measure of complexity” is a seminal research paper by Andrew Yao that laid foundational concepts in computational complexity theory, particularly regarding the role and analysis of randomness in algorithms.

A. Blum complexity measures
Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
B. Computational Complexity: A Conceptual Perspective
Computational Complexity: A Conceptual Perspective is a graduate-level textbook that presents the foundations and key themes of computational complexity theory with an emphasis on conceptual understanding over technical detail.
C. Randomness and Computation
"Randomness and Computation" is Shafi Goldwasser's influential doctoral thesis that helped lay the foundations of modern complexity theory and cryptography by rigorously exploring the role of randomness in efficient computation.
D. Kolmogorov complexity
Kolmogorov complexity is a measure of the amount of information in an object, defined as the length of the shortest computer program that can produce it.
E. P, NP, and NP-Completeness: The Basics of Complexity Theory
"P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
F. None of above. chosen

Statements (35)

Predicate	Object
instanceOf	research paper ⓘ scientific article ⓘ
author	Andrew Chi-Chih Yao ⓘ linked to: Andrew Yao Andrew Yao ⓘ
citedFor	formal treatment of probabilistic computation models ⓘ foundational role in the theory of randomized algorithms ⓘ framework for comparing probabilistic and deterministic algorithms ⓘ
contribution	analyzed the power of probabilistic algorithms compared to deterministic algorithms ⓘ formalized the role of randomness in computational complexity ⓘ helped define and clarify probabilistic complexity classes ⓘ introduced a unified framework for measuring the complexity of probabilistic computations ⓘ
describedAs	a seminal research paper that laid foundational concepts in computational complexity theory regarding randomness in algorithms ⓘ
field	computational complexity theory ⓘ computer science ⓘ theoretical computer science ⓘ
hasShortTitle	Probabilistic computations ⓘ linked to: “Probabilistic computations: Toward a unified measure of complexity”
hasTitle	Probabilistic computations: Toward a unified measure of complexity ⓘ linked to: “Probabilistic computations: Toward a unified measure of complexity”
impact	considered a seminal work in computational complexity theory ⓘ influenced later research on randomized algorithms ⓘ influenced the study of the relationship between deterministic and probabilistic computation ⓘ
influencedBy	earlier work on Turing machines and complexity measures ⓘ
language	English ⓘ
relatedTo	algorithm analysis ⓘ deterministic complexity theory ⓘ randomized complexity classes such as RP and BPP ⓘ
studies	probabilistic models of computation ⓘ the complexity of algorithms that use randomization ⓘ
topic	complexity classes ⓘ probabilistic Turing machines ⓘ probabilistic computation ⓘ randomized algorithms ⓘ randomness in computation ⓘ
usedIn	graduate-level courses in computational complexity ⓘ research on complexity class separations ⓘ research on derandomization ⓘ

How these facts were elicited

Referenced by (3)

Full triples — surface form annotated when it differs from this entity's canonical label.

Andrew Yao → notableWork → “Probabilistic computations: Toward a unified measure of complexity” ⓘ

Probabilistic computations: Toward a unified measure of complexity → hasTitle → Probabilistic computations: Toward a unified measure of complexity ⓘ

subject linked to: “Probabilistic computations: Toward a unified measure of complexity”

linked to: “Probabilistic computations: Toward a unified measure of complexity”

Probabilistic computations: Toward a unified measure of complexity → hasShortTitle → Probabilistic computations ⓘ