Sciweavers

TSMC
2010
12 years 11 months ago
Invariant Set of Weight of Perceptron Trained by Perceptron Training Algorithm
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...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Herber...
NAACL
2010
13 years 2 months ago
Distributed Training Strategies for the Structured Perceptron
Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
Ryan T. McDonald, Keith Hall, Gideon Mann
IJCES
2002
100views more  IJCES 2002»
13 years 4 months ago
Neural Network Decoders for Linear Block Codes
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...
Ja-Ling Wu, Yuen-Hsien Tseng, Yuh-Ming Huang
JMLR
2007
101views more  JMLR 2007»
13 years 4 months ago
Noise Tolerant Variants of the Perceptron Algorithm
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...
Roni Khardon, Gabriel Wachman
TNN
2008
96views more  TNN 2008»
13 years 4 months ago
Global Convergence and Limit Cycle Behavior of Weights of Perceptron
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...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Hak-Ke...
SIAMCOMP
2008
140views more  SIAMCOMP 2008»
13 years 4 months ago
The Forgetron: A Kernel-Based Perceptron on a Budget
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...
Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
NECO
2008
101views more  NECO 2008»
13 years 4 months ago
On the Classification Capability of Sign-Constrained Perceptrons
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...
Robert A. Legenstein, Wolfgang Maass
JSA
2006
108views more  JSA 2006»
13 years 4 months ago
Improved composite confidence mechanisms for a perceptron branch predictor
In 2001, Jime
Veerle Desmet, Lieven Eeckhout, Koen De Bosschere
ACL
2004
13 years 5 months ago
Incremental Parsing with the Perceptron Algorithm
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...
Michael Collins, Brian Roark
COLT
1997
Springer
13 years 8 months ago
General Convergence Results for Linear Discriminant Updates
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...
Adam J. Grove, Nick Littlestone, Dale Schuurmans