2924 search results - page 166 / 585 » On the Use of Evidence in Neural Networks |
99
Voted
IWANN
1999
Springer
15 years 6 months ago
1999
Springer
In this paper, a new algorithm for blind inversion of Wiener systems is presented. The algorithm is based on minimization of mutual information of the output samples. This minimiz...
111
Voted
NIPS
2001
15 years 3 months ago
2001
This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage learning and directed exploration can...
108
click to vote
NC
2010
15 years 7 days ago
2010
This paper presents two approaches based on metabolic and stochastic P systems, together with their associated analysis methods, for modelling biological systems and illustrates th...
132
Voted
ICANN
2011
Springer
14 years 5 months ago
2011
Springer
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
125
click to vote
ICANN
2009
Springer
15 years 6 months ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...