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» The Bias Problem and Language Models in Adaptive Filtering
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TNN
2008
177views more  TNN 2008»
13 years 7 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
ICIAP
2007
ACM
14 years 7 months ago
Adaptive uncertainty estimation for particle filter-based trackers
In particle filter?based visual trackers, dynamic velocity components are typically incorporated into the state update equations. In these cases, there is a risk that the uncertai...
Andrew D. Bagdanov, Alberto Del Bimbo, Fabrizio Di...
ICASSP
2009
IEEE
14 years 2 months ago
Resampling auxiliary data for language model adaptation in machine translation for speech
Performance of n-gram language models depends to a large extent on the amount of training text material available for building the models and the degree to which this text matches...
Sameer Maskey, Abhinav Sethy
SIGIR
2009
ACM
14 years 2 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
KES
2007
Springer
14 years 1 months ago
Fuzzy Adaptive Particle Filter for Localization of a Mobile Robot
Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of localization are due to uncertainties in the modelin...
Young-Joong Kim, Chan-Hee Won, Jung-Min Pak, Myo-T...