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ICANN
2009
Springer
15 years 10 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
ATMOS
2007
152views Optimization» more  ATMOS 2007»
15 years 7 months ago
Solution of the Train Platforming Problem
In this paper we study a general formulation of the train platforming problem, which contains as special cases all the versions previously considered in the literature as well as a...
Alberto Caprara, Laura Galli, Paolo Toth
BC
2007
107views more  BC 2007»
15 years 6 months ago
Decoding spike train ensembles: tracking a moving stimulus
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Enrico Rossoni, Jianfeng Feng
INTERSPEECH
2010
15 years 1 months ago
A classifier-based target cost for unit selection speech synthesis trained on perceptual data
Our goal is to automatically learn a perceptually-optimal target cost function for a unit selection speech synthesiser. The approach we take here is to train a classifier on human...
Volker Strom, Simon King
ECCV
2006
Springer
16 years 8 months ago
Towards Optimal Training of Cascaded Detectors
Cascades of boosted ensembles have become popular in the object detection community following their highly successful introduction in the face detector of Viola and Jones [1]. In t...
S. Charles Brubaker, Matthew D. Mullin, James M. R...