Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naïve Bayesian classification algorithms. The architecture of our s...
We introduce an adaptive generalized selection combining (A-GSC) receiver that can be efficiently applied in diversity rich fading environments such as in ultra-wideband applicatio...
Athanasios S. Lioumpas, George K. Karagiannidis, T...
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
Pricing has become one of the main challenges of the networking community and is receiving a great deal of interest in the literature. In this paper, we analyze the so-called Pari...