TSMC
2010
13 years 7 months ago
2010
In this paper, an invariant set of the weight of the perceptron trained by the perceptron training algorithm is defined and characterized. The dynamic range of the steady state va...
NAACL
2010
13 years 10 months ago
2010
Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
IJCES
2002
14 years 15 days ago
2002
This paper presents a class of neural networks suitable for the application of decoding error-correcting codes.The neural model is basically a perceptron with a high-order polynom...
JMLR
2007
14 years 19 days ago
2007
A large number of variants of the Perceptron algorithm have been proposed and partially evaluated in recent work. One type of algorithm aims for noise tolerance by replacing the l...
TNN
2008
14 years 19 days ago
2008
In this paper, it is found that the weights of a perceptron are bounded for all initial weights if there exists a nonempty set of initial weights that the weights of the perceptron...
SIAMCOMP
2008
14 years 20 days ago
2008
Abstract. The Perceptron algorithm, despite its simplicity, often performs well in online classification tasks. The Perceptron becomes especially effective when it is used in conju...
NECO
2008
14 years 20 days ago
2008
The perceptron (also referred to as McCulloch-Pitts neuron, or linear threshold gate) is commonly used as a simplified model for the discrimination and learning capability of a bi...
JSA
2006
14 years 21 days ago
2006
In 2001, Jime
ACL
2004
14 years 2 months ago
2004
This paper describes an incremental parsing approach where parameters are estimated using a variant of the perceptron algorithm. A beam-search algorithm is used during both traini...
COLT
1997
Springer
14 years 4 months ago
1997
Springer
The problem of learning linear discriminant concepts can be solved by various mistake-driven update procedures, including the Winnow family of algorithms and the well-known Percep...