In this paper, a discriminant hidden Markov model is de- fined and it is shown how a particular multilayer perceptron with contextual and extra feedback input ...
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Discriminative learning techniques for sequen- tial data have proven to be more effective than generative models for named entity recognition,.
The statistical use of a particular classic form of a connectionist system, the multilayer perceptron (MLP), is described in the context of the recognition ...
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The multi-view approach is based on the principle of maximizing the consensus among multiple independent hy- potheses; we develop this principle into a semi- ...
Previous work has shown the ability of Srtificial Neural Networks (ANNs), and Multilayer Perceptrons (MLPs) in particular, to estimate a posteriori ...
In this work, the neural network in the HNN is a feed-forward multilayer perceptron network (MLP) with one hidden layer. The input layer uses the sigmoid ...
4 Multi-View Hidden Markov Perceptrons. In this section we present the dual multi-view hidden Markov perceptron algorithm. For the reader's convenience ...
In the present paper we will be studying the contributions that neural networks, and more specifically multilayer perceptrons (MLP), have made to time series.
Abstract—Recently, multi-view representation learning has become a rapidly growing direction in machine learning and data mining.
... Multi-view learning refers to a set of semi-supervised methods which exploit redundant views of the same input data (Blum and Mitchell, 1998;Collins and ...