The process of learning an unknown distribution from examples is usually called denszty estimation or parameter estimation in statistics, depending on the ...

Unsupervised learning of distributions on binary vectors using two layer networks. Part of Advances in Neural Information Processing Systems 4 (NIPS 1991).

Jun 22, 1994 · The neural network implementation of P CA is usually a two layer network with the same architecture as the combination model. The learning rule, ...

The second learning algorithm is a greedy method that creates the hidden units and computes their weights one at a time. This method is a variant of the ...

Unsupervised learning of distributions on binary vectors using two layer networks. Yoav Freund, David Haussler, 1994. Presented By: Yaoguang Zhai. Page 2 ...

It is shown that arbitrary distributions of binary vectors can be approximated by the combination model and shown how the weight vectors in the model can be ...

Jun 22, 1994 · We present a distribution model for binary vectors, called the in uence combination model and show how this model can be used as the basis ...

We present a distribution model for binary vectors, called the influence combination model and show how this model can be used as the basis for unsupervised ...

Freund, Y. and Haussler, D. (1994) Unsupervised Learning of Distributions of Binary Vectors Using Two Layer Networks.

ABSTRACT: In this paper, we provide a new approach to classify and recognize the acoustic events for multiple autonomous robots systems based on the deep ...