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Asymptotically optimal algorithm

In computer science, an algorithm is said to be asymptotically optimal if, roughly speaking, for large inputs it performs at worst a constant factor (independent of the input size) worse than any possible algorithm. It is a term commonly encountered in computer science research as a result of widespread use of big O notation.

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Asymptotically optimal algorithm

Nodes34
Edges33
Triples16
Avg. degree1.94
Density0.058824
Components1

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Asymptotically optimal algorithm

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related to Speedup · 10
Asymptotically optimal algorithm → Ackermann, Blum's, Coppersmith, For, However, Omega, Strassen-type, The, Whether, Winograd

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optimal asymptotically algorithm algorithms input inputs use example data may time problem computer constant possible require comparisons range practice better

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SubjectPredicateObjectConfidenceSrc
better performance on specific inputsinstance ofNew algorithms may also present advantages0.80text
decreased use of other resourcesinstance ofNew algorithms may also present advantages0.80text
or being simpler to describeinstance ofNew algorithms may also present advantages0.80text
implementinstance ofNew algorithms may also present advantages0.80text
memory cacheinstance ofhardware optimizations0.80text
parallel processing may beinstance ofhardware optimizations0.80text
Asymptotically optimal algorithmrelated to SpeedupThe0.60section
Asymptotically optimal algorithmrelated to SpeedupBlum's0.60section
Asymptotically optimal algorithmrelated to SpeedupHowever0.60section
Asymptotically optimal algorithmrelated to SpeedupFor0.60section
Asymptotically optimal algorithmrelated to SpeedupAckermann0.60section
Asymptotically optimal algorithmrelated to SpeedupOmega0.60section

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