107 search results - page 14 / 22 » Learning to rank using gradient descent |
110
Voted
COLT
2000
Springer
15 years 4 months ago
2000
Springer
In this paper we examine master regression algorithms that leverage base regressors by iteratively calling them on modified samples. The most successful leveraging algorithm for c...
81
Voted
ML
2002
ACM
15 years 10 days ago
2002
ACM
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
105
Voted
ISNN
2007
Springer
15 years 6 months ago
2007
Springer
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
108
Voted
ESANN
2003
15 years 2 months ago
2003
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
149
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NCA
2006
IEEE
15 years 18 days ago
2006
IEEE
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks...