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» Minimization of Error Functionals over Perceptron Networks
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IJCNN
2006
IEEE
15 years 3 months ago
High-speed Bi-directional Function Approximation using Plausible Neural Networks
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen
JMLR
2006
107views more  JMLR 2006»
14 years 9 months ago
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
Di-Rong Chen, Tao Sun
ICASSP
2011
IEEE
14 years 1 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
JCM
2008
109views more  JCM 2008»
14 years 9 months ago
Performance and Capacity Analysis of UWB Networks over 60GHz WPAN Channel
In this paper we evaluate the system performance and capacity of single carrier ultra-wideband (UWB) networks over 60GHz wireless personal area network (WPAN) channel. Symbol error...
Wei Li 0007, Jun Wei, Michael Smith
CORR
2006
Springer
154views Education» more  CORR 2006»
14 years 9 months ago
Functional Bregman Divergence and Bayesian Estimation of Distributions
Abstract--A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functi...
B. A. Frigyik, Santosh Srivastava, Maya R. Gupta