We apply two acceleration techniques for the backpropagation algorithm to an iterative gradient descent algorithm called the network inversion algorithm. Experimental results show that these techniques are also quite effective to decrease the number of iterations required for the detection of input vectors on the classification boundary of a multilayer perceptron.
|Number of pages||4|
|Journal||IEICE Transactions on Information and Systems|
|Publication status||Published - 1999|
- Active learning based on existing training examples
- Classification problems
- Multilayer perceptrons
- The network inversion algorithm