The Cyclotron (Mann, W. B.)

W 3 , b 3 ) ( W ′ 3 , b ′ 3 ) ( W ′ 2 , b ′ 2 ) ( W ′ 1 , b ′ 1 ) ( W ′ ′

In this paper, we present a deep neural network (DNN)-based acoustic scene classification framework. Two hierarchical learning methods are proposed to improve the DNN baseline performance by incorporating the hierarchical taxonomy information of environmental sounds. Firstly, the parameters of the DNN are initialized by the proposed hierarchical pre-training. Multi-level objective function is t...

W A B W A B Input Hidden Output

A modiication to neural network training algorithms is proposed which decorrelates certain weights within the network while minimising the mean squared error. The technique was developed to facilitate neural network interpretation in image processing problems, partly by allowing to initialise all network weights with one xed, low value. However, it can also be applied to classiica-tion tasks in...

The Equivalence between Mann and Implicit Mann Iterations

We shall prove the equivalence bewteen the convergences of Mann and implicit Mann iterations dealing with various classes of non-Lipschitzian operators.

The Mann - Grubbs Method

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