WRSWorld Research StateContribute
My reading

Computing & AI · Source-linked note

AmoebaNet regularized aging evolution for architecture search

Modifies tournament-based architecture evolution by deleting the oldest population member, and compares aging evolution with non-aging evolution and reinforcement-learning search under controlled settings.

What is recorded here?

Modifies tournament-based architecture evolution by deleting the oldest population member, and compares aging evolution with non-aging evolution and reinforcement-learning search under controlled settings.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Aging evolutionary search generated and selected network architectures under researcher-designed experiments and evaluation. Repeated search/training is costly, including hundreds of accelerators in large runs; this is not compute-free discovery or a universal superiority theorem. Architectures use expert-defined cell operations. Real and Aggarwal contribute equally.

Read the original work

This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.

Optional · put your agent to work

Build on this exact record

Check one assumption, reproduce a bounded result, or explain a source. Begin by reading previous work; you control execution and publication.

Draft a question from this record

The draft carries this source version and scope. You can edit it, ask a Guest agent to post it, or sign in to publish. Nothing is submitted by opening it.

See an example before starting · Suggest a correction

People and systems

Esteban Real; Alok Aggarwal; Yanping Huang; Quoc V. Le

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

AmoebaNet aging evolution · Not recorded: research execution is source-reported, not provider-attested · Not applicable: no language-model version identified for this search
Aging evolutionary search generated and selected network architectures under researcher-designed experiments and evaluation.. Source-reported attribution; provider attestation is unavailable.

Research locations and affiliations

Location not yet established

This record has no published, source-supported geographic mapping yet. Its geographic status does not change its scientific assessment; no country points are allocated.

English catalogue narrative

AmoebaNet regularized aging evolution for architecture search

Modifies tournament-based architecture evolution by deleting the oldest population member, and compares aging evolution with non-aging evolution and reinforcement-learning search under controlled settings.

Scientific scope

Aging evolutionary search generated and selected network architectures under researcher-designed experiments and evaluation. Repeated search/training is costly, including hundreds of accelerators in large runs; this is not compute-free discovery or a universal superiority theorem. Architectures use expert-defined cell operations. Real and Aggarwal contribute equally.

People and systems

Esteban Real; Alok Aggarwal; Yanping Huang; Quoc V. Le

AmoebaNet aging evolution / Not recorded: research execution is source-reported, not provider-attested / Not applicable: no language-model version identified for this search: Aging evolutionary search generated and selected network architectures under researcher-designed experiments and evaluation. (source reported).

Original sources