30 search results - page 3 / 6 » Overfitting and Neural Networks: Conjugate Gradient and Back... |
NPL
2000
13 years 5 months ago
2000
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate is derived. The algorithm is based upon minimising the instantaneous output erro...
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. This paper presents Recurrent Policy Gradients, a modelfree reinforcement learning (RL) method creating limited-memory stochastic policies for partially observable Markov...
JMLR
2012
11 years 7 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
ML
2006
ACM
13 years 5 months ago
2006
ACM
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
ICAISC
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. We propose a non-standard neural network called TPNN which offers the direct mapping from a peptide sequence to a property of interest in order to model the quantitative ...