In this paper we discuss a general framework for feature selection based on nonparametric statistics. The three stage approach we propose is based on the assumption that the avail...
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
In this work, a Bayesian framework for OFDM channel estimation is proposed. Using the maximum entropy principle to exploit prior system information at the receiver, we successively...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Statistical language modeling (SLM) has been used in many different domains for decades and has also been applied to information retrieval (IR) recently. Documents retrieved using...