HESSPROP: Mitigating Memristive DNN Weight Mapping Errors with Hessian Backpropagation
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Bibliographic record
Abstract
A universal objective function to minimize mem-ristive crossbar deep neural network weight mapping errors through Hessian backpropagation (HessProp) is presented. Hes-sProp minimizes the <tex>$L_{2}$</tex> norm of the neural network gradient to achieve a flat minima in a neural network's weight space. We hypothesize that this leads to robustness against small perturbations of weights. The stochastic weight mapping phe-nomenon on memristor crossbars is simulated, and the proposed method was evaluated on image classification tasks using the MNIST dataset. The result demonstrates on average 40.81% and 41.45% groundbreaking accuracy increase for distilled and large memristive convolutional neural networks in worst-case scenarios.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it