Deep neural networks (DNNs) have begun to have a pervasive impact on various
applications of machine learning. However, the problem of finding an optimal DNN …

The neural network with optimal architecture speeds up the learning process and
generalizes the problem well for further knowledge extraction. As a result researchers have …

: Yapay sinir ağları, sınıflandırma, modelleme ve tahmin gibi birçok günlük hayat probleminin
çözümünde başarılı sonuç veren bir yöntemdir. Yapay sinir ağları birimler arasındaki …

In this paper, we propose a group Lasso regularization term as a hidden layer regularization
method for feedforward neural networks. Adding a group Lasso regularization term into the …

Optimizing the structure of neural networks is an essential step for the discovery of
knowledge from data. This paper deals with a new approach which determines the …

Traditionally, deep learning algorithms update the network weights, whereas the network
architecture is chosen manually using a process of trial and error. In this paper, we propose …

Music is part of many areas throughout daily life, from entertainment to rehabilitation.
Technological developments are widely used in music, as they are in every field. In this …

Bu makalede, bir gizli katmanlı yapay sinir ağları için optimal nöron sayısı araştırılmıştır.
Bunun için teorik ve istatiksel çalışmalar yapılmıştır. Optimal nöron sayısını bulmak için …

Quality control is important in the industry and its importance increases with each passing
year. In today's industry, the defect of the products produced can create very important …

We introduce a novel weight pruning methodology for MLP classifiers that can be used for
model and/or feature selection purposes. The main concept underlying the proposed …