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Diffstat (limited to 'RAIN_EP_DILLAVOU_MATRIX.md')
| -rw-r--r-- | RAIN_EP_DILLAVOU_MATRIX.md | 15 |
1 files changed, 10 insertions, 5 deletions
diff --git a/RAIN_EP_DILLAVOU_MATRIX.md b/RAIN_EP_DILLAVOU_MATRIX.md index 094d9d6..3fe39e2 100644 --- a/RAIN_EP_DILLAVOU_MATRIX.md +++ b/RAIN_EP_DILLAVOU_MATRIX.md @@ -2,8 +2,11 @@ ## Question -Can a local neutral predictor remove a fixed hardware update offset without -using a larger EP nudging voltage? +The fixed-offset experiment is only an implementation sanity check. With an +exact neutral observation, subtracting a strictly constant offset is already +an oracle and cannot demonstrate an SDIL advantage. The scientific question +is whether SDIL improves downstream accuracy when local hardware bias changes +with device state and a stored constant is therefore insufficient. The primary corruption is the model in Dillavou et al., Eq. (7). Every local parameter update receives a fixed, unknown, parameter-specific offset after @@ -20,9 +23,11 @@ state-drift ratio is zero in all exact-model experiments. The correction is local and uses no backpropagation. With the teaching input disabled, the update circuit exposes `B_i`. The predictor stores this neutral -measurement and subtracts it from subsequent updates. Under the strictly -constant model, constant calibration and SDIL innovation are expected to -coincide. A difference between them is neither predicted nor claimed. +measurement and subtracts it from subsequent updates. Under the strictly +constant model, constant calibration, SDIL innovation, and oracle subtraction +are equivalent after the exact neutral observation. A difference between them +is neither predicted nor claimed, and recovery in this setting is not evidence +for SDIL. ## Frozen author protocol |
