Estimating the generalization error is one of the key ingredients of supervised learning since a good generalization error estimator can be used for model selection. An unbiased g...
In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a ...
We designed subthreshold analog MOS circuits implementing an inhibitory network model that performs noise-shaping pulse-density modulation with noisy neural elements. Our aim is t...