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» PAC-Bayesian learning of linear classifiers
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ICMLA
2008
13 years 9 months ago
New Insights into Learning Algorithms and Datasets
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
Jun Won Lee, Christophe G. Giraud-Carrier
NIPS
2008
13 years 9 months ago
Exact Convex Confidence-Weighted Learning
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Koby Crammer, Mark Dredze, Fernando Pereira
ICIP
2001
IEEE
14 years 9 months ago
Region-based approach for discriminant snakes
This paper proposes a statistic framework for segmenting textured areas over real images by discriminant snakes. Our active contour model has the ability to learn different textur...
Jordi Vitrià, Petia Radeva
EMNLP
2010
13 years 5 months ago
Confidence in Structured-Prediction Using Confidence-Weighted Models
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Avihai Mejer, Koby Crammer
ICML
2010
IEEE
13 years 5 months ago
The Margin Perceptron with Unlearning
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
Constantinos Panagiotakopoulos, Petroula Tsampouka