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Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
Reservoir computing (RC) is a machine learning algorithm that can learn complex time series from data very rapidly based on the use of high-dimensional dynamical systems, such as random networks of neurons, called "reservoirs."
A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design
We also propose several techniques to improve the performance on a recognition task, and show that the classification accuracy of the proposed algorithm is as high as that of the state-of-the-art temporal coding SNN algorithms on the MNIST dataset.
Predicting Glaucoma Visual Field Loss by Hierarchically Aggregating Clustering-based Predictors
Thus, we propose a method for aggregating cluster-based predictors to obtain better prediction accuracy than from a single cluster-based prediction.
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