A piecewise asymmetric variance penalty added to EVCL yields marginal accuracy gains on MNIST-family benchmarks, with several ties and no reported uncertainty.
Connectionist models of recognition memory: Con- straints imposed by learning and forgetting functions,
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Adaptive Variance-Penalized Continual Learning with Fisher Regularization
A piecewise asymmetric variance penalty added to EVCL yields marginal accuracy gains on MNIST-family benchmarks, with several ties and no reported uncertainty.