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TNN
2008
177views more  TNN 2008»
15 years 6 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
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...
Yoshua Bengio, Jean-Sébastien Senecal
JIPS
2007
92views more  JIPS 2007»
15 years 6 months ago
Optimization of Domain-Independent Classification Framework for Mood Classification
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...
Sung-Pil Choi, Yuchul Jung, Sung-Hyon Myaeng
TWC
2008
101views more  TWC 2008»
15 years 6 months ago
Adaptive generalized selection combining (A-GSC) receivers
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...
ASC
2004
15 years 6 months ago
Neural network-based colonoscopic diagnosis using on-line learning and differential evolution
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...
CN
2004
102views more  CN 2004»
15 years 6 months ago
A mathematical model of the Paris Metro Pricing scheme for charging packet networks
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...
David Ros, Bruno Tuffin