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» Learning associative Markov networks
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HIS
2008
15 years 7 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
André L. D. Rossi, André C. P. L. F....
IJCNN
2006
IEEE
15 years 11 months ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...
MICAI
2005
Springer
15 years 11 months ago
Modelling Human Intelligence: A Learning Mechanism
We propose a novel, high-level model of human learning and cognition, based on association forming. The model configures any input data stream featuring a high incidence of repeti...
Enrique Carlos Segura, Robin W. Whitty
FOCI
2007
IEEE
16 years 4 hour ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh
ICML
2007
IEEE
16 years 6 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...