Neural Fisher Discriminant Analysis


Neural Fisher Discriminant Analysis – Neural network models contain two main components, classification and segmentation, which are very similar but which are not easily distinguishable. Classifying the network structure can be tedious and time consuming, especially for large networks. This work tackles the task of classifying a large set of MNIST digits using neural networks (NN). We first propose a neural network model of MNIST digits which has a multi-layer perceptron for classification. Then we apply a neural network to classify MNIST digits using a multi-task learning algorithm. Experimental results demonstrate that the proposed model outperforms the state-of-the-art MNIST digits classification method.

This paper presents a comprehensive survey of the major knowledge bases from linguistics and bioinformatics of the country of Sri Lanka. Most of the text is a short survey about the knowledge base itself and how people interpret the information present there.

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Neural Fisher Discriminant Analysis

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    Linguistic features of a language: a surveyThis paper presents a comprehensive survey of the major knowledge bases from linguistics and bioinformatics of the country of Sri Lanka. Most of the text is a short survey about the knowledge base itself and how people interpret the information present there.


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