Generative Stochastic Networks (GSN) for supervised tasks generalize the denoising autoencoders by fixing the deepest layer to the output variables (e.g. class) and estimate the input output joint distribution as the stationary transition operator of a Markov chain.
In fact, low purity vertices are usually found in boundary regions between components of different classes in supervised tasks.
Each session was organized to maximize the engagement of the patient by offering a range of shorter closely supervised tasks.
JK conceived of the study, supervised task development, recruitment and data collection, performed statistical analyses and drafted the manuscript.
The basic idea is to perform multi-task learning on a supervised classification task and a semi-supervised auxiliary task.
The basic idea is to perform multitask learning on a supervised classification task and a semi-supervised auxiliary task via a regularization term.
Here, we try to improve the classification accuracy of SVM, this is a supervised task, so PLS a supervised method is superior to PCA, an unsupervised method.
The overall goal of the auxiliary task is to improve accuracy on the supervised task by uncovering hidden structures in the original data.
The computation of kernels forms the unsupervised preprocessing component and is key for the superior performance of the neural response algorithm as it can minimize the complexity of the corresponding image classification problem (supervised task)[ 28].
However, we showed that this defect can be transformed into a merit through combination with supervised classifiers like SVM, where the tuning parameter such as a kernel parameter can be used to enhance sample discrimination in relation to the aim of the supervised task.
