In the anisotropic two-feature toy problem, vanilla GD rapidly fits the training data but can retain chance-level or very poor test performance for a long plateau. With distribution shift, the reported plateau scales as order 1/(eta epsilon) for large initialization and order (1/eta) log(1/(tau epsilon)) for small initialization; with identical train and test distributions it again scales as order 1/(eta epsilon).

In the anisotropic two-feature toy problem, vanilla GD rapidly fits the training data but can retain chance-level or very poor test performance for a long plateau. With distribution shift, the reported plateau scales as order 1/(eta epsilon) for large initialization and order (1/eta) log(1/(tau epsilon)) for small initialization; with identical train and test distributions it again scales as order 1/(eta epsilon). · CiteArk

Measurement results

0/1 assessed

0 supported0 disputed or conflicting1 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Metric and conditions	Reported	Latest observation	Evidence judgment
	100%	—	Not assessed

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results