PatchEchoClassifier combines an echo state network with DeiT-style distillation from an MLP-Mixer teacher to reach about 86% accuracy on SHL human activity data at much lower FLOPs, though it falls below 80% on four other public HAR datasets.
Dataset for ADL Recognition with Wrist-worn Ac- celerometer
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Knowledge Distillation for Reservoir-based Classifier: Human Activity Recognition
PatchEchoClassifier combines an echo state network with DeiT-style distillation from an MLP-Mixer teacher to reach about 86% accuracy on SHL human activity data at much lower FLOPs, though it falls below 80% on four other public HAR datasets.