Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
This study tested the effectiveness of audio-visual training in the discrimination of the phonetic feature of voicing on the recognition of written words by young children deemed ...
Background: Establishment of peptide binding to Major Histocompatibility Complex class I (MHCI) is a crucial step in the development of subunit vaccines and prediction of such bin...
Ana Paula Sales, Georgia D. Tomaras, Thomas B. Kep...
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
In discriminative training, such as Maximum Mutual Information Estimation (MMIE) training, a word lattice is usually used as a compact representation of many different sentence hy...
Abstract. Validation can be used to detect when over tting starts during supervised training of a neural network; training is then stopped before convergence to avoid the over ttin...
Abstract. Virtual training systems are increasingly used for the training of complex, dynamic tasks. To give trainees the opportunity to train autonomously, intelligent agents are ...
Anyone who works with student employees knows that while it is often difficult to train sufficiently, it is of the utmost importance to have a qualified, knowledgeable staff. We w...
The DEFACTO system is a multiagent based tool for training incident commanders for large scale disasters. In this paper, we highlight some of the lessons that we have learned from...
Nathan Schurr, Pratik Patil, Frederic H. Pighin, M...
The quality of student consultants and their development through training and education are major factors in determining long-term effectiveness of university Help Desk. To hire a...