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IJON
2010
109views more  IJON 2010»
13 years 2 months ago
Variational inference for Student-t MLP models
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...
Hang T. Nguyen, Ian T. Nabney
ICDM
2003
IEEE
105views Data Mining» more  ICDM 2003»
14 years 1 months ago
SVM Based Models for Predicting Foreign Currency Exchange Rates
Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA bas...
Joarder Kamruzzaman, Ruhul A. Sarker, Iftekhar Ahm...
ICASSP
2011
IEEE
12 years 11 months ago
Non-negative matrix deconvolution in noise robust speech recognition
High noise robustness has been achieved in speech recognition by using sparse exemplar-based methods with spectrogram windows spanning up to 300 ms. A downside is that a large exe...
Antti Hurmalainen, Jort F. Gemmeke, Tuomas Virtane...
IWANN
2001
Springer
14 years 13 days ago
Is Neural Network a Reliable Forecaster on Earth? A MARS Query!
: Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and ...
Ajith Abraham, Dan Steinberg
CORR
2011
Springer
136views Education» more  CORR 2011»
12 years 11 months ago
Eliciting Forecasts from Self-interested Experts: Scoring Rules for Decision Makers
Scoring rules for eliciting expert predictions of random variables are usually developed assuming that experts derive utility only from the quality of their predictions (e.g., sco...
Craig Boutilier