Training of artificial neuronal networks with nonlinear optimization techniques

Thierry Tchouto Mbatchou
Machine learning is a field that has been the object of study of many researchers around the globe during the last decades. Very often to solve machine learning challenges like classification problems for example, one needs to train an artificial neural network. To train this network a certain loss function has to be minimized. There is a ubiquitous approach to achieve this which consists of using variants of the stochastic gradient descent combined with the backpropagation algorithm. In our
more » ... k, we aimed at testing a rather non-conventional scheme consisting of making use of the solvers a software called AMPL offers.
doi:10.26127/btuopen-5404 fatcat:ib2qidpc6jgpvbnq6lc45ntosi