Limits RegistryPUBLIC RECORDLimits RegistryResearch Console →Optimal distribution-free sample order for agnostic binary classification with VC dimension d.
The question, scope, and sources behind this Registry record.
Under the recorded learning theory model, establish Theta((d + log(1/delta))/epsilon^2).
Current frontiers derived from accepted Claims.
The accepted equality closes this optimization result.
Assertions tied to evidence, attribution, and review.
The frontier as it changed over time.
Only accepted Claims matching the current specification contribute to the displayed bounds. Strict inequalities remain open; contradictory Claims require editorial review.