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COLT
2005
Springer
14 years 3 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
EMNLP
2007
13 years 11 months ago
A Sequence Alignment Model Based on the Averaged Perceptron
We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in co...
Dayne Freitag, Shahram Khadivi
CORR
2008
Springer
80views Education» more  CORR 2008»
13 years 9 months ago
Multi-Layer Perceptrons and Symbolic Data
In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multila...
Fabrice Rossi, Brieuc Conan-Guez
IJON
2008
105views more  IJON 2008»
13 years 8 months ago
Estimating the number of components in a mixture of multilayer perceptrons
BIC criterion is widely used by the neural-network community for model selection tasks, although its convergence properties are not always theoretically established. In this paper...
Madalina Olteanu, Joseph Rynkiewicz
CIS
2005
Springer
14 years 3 months ago
Training Multi-layer Perceptrons Using MiniMin Approach
Abstract. Multi-layer perceptrons (MLPs) have been widely used in classification and regression task. How to improve the training speed of MLPs has been an interesting field of res...
Liefeng Bo, Ling Wang, Licheng Jiao