What is recorded here?
Optimized an approximate min-max neighborhood-loss objective by perturbing weights along a first-order direction and computing an update gradient at the perturbed weights.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Inherits sharpness/generalization and robust-optimization ideas. Practical inner maximization and gradient omit higher-order terms; two gradient evaluations add cost. This does not globally solve the min-max problem or guarantee improved generalization on every task/reparameterization.
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People and systems
Pierre Foret; Ariel Kleiner; Hossein Mobahi; Behnam Neyshabur
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.
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English catalogue narrative
SAM: approximate neighborhood-loss minimization
Optimized an approximate min-max neighborhood-loss objective by perturbing weights along a first-order direction and computing an update gradient at the perturbed weights.
Scientific scope
Inherits sharpness/generalization and robust-optimization ideas. Practical inner maximization and gradient omit higher-order terms; two gradient evaluations add cost. This does not globally solve the min-max problem or guarantee improved generalization on every task/reparameterization.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Pierre Foret; Ariel Kleiner; Hossein Mobahi; Behnam Neyshabur
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.