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That is, the output of each layer serves as a prior for learning the parameters of the next higher layer.
One set (of size M L ) is used for learning the parameters of the statistical model, on the basis of which the design is defined.
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Techniques that connect acoustic content to semantic concepts present an additional challenge, in that learning the parameters of the retrieval system becomes a supervised learning problem as each training set sound file must have semantic labels for parameter learning.
To account for the local baseline, they applied their HMM to overlapping segments of 40 probes, and for each segment, they learned the parameters of the model separately.
Given labeled expression data we can learn the parameters of a HMM using the Baum Welch algorithm for each of the three topologies mentioned above.
We developed an iterative learning procedure to learn the parameters of our model and a multi-task learning method for combining data from multiple conditions.
The training set is used for learning to fit the parameters of the classifier.
CWN typically utilizes adaptive frameworks such as reinforcement learning, learning automata, game theory, etc., for adaptively optimizing the parameters of the network.
For one: the parameters of the trials.
These parameters are used for "learning" the two proposed SVMs.
We use a co-training approach to iteratively learn the parameters for two models of microarray similarity, each of which uses a different set of features as input.
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