Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...
The integrated approach is a classifier established on statistical estimator and artificial neural network. This consists of preliminary data whitening transformation which provide...
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
We consider the multi-class classification problem, based on vector observation sequences, where the conditional (given class observations) probability distributions for each class...