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» Lazy Transformation-Based Learning
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ICML
2000
IEEE
14 years 8 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
CORR
2000
Springer
132views Education» more  CORR 2000»
13 years 7 months ago
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
This paper describes a set of comparative experiments, including cross{corpus evaluation, between ve alternative algorithms for supervised Word Sense Disambiguation (WSD), namely ...
Gerard Escudero, Lluís Màrquez, Germ...
ML
2008
ACM
13 years 7 months ago
Unrestricted pure call-by-value recursion
Call-by-value languages commonly restrict recursive definitions by only allowing functions and syntactically explicit values in the right-hand sides. As a consequence, some very a...
Johan Nordlander, Magnus Carlsson, Andy Gill
ESWA
2008
134views more  ESWA 2008»
13 years 6 months ago
Neighborhood classifiers
K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for...
Qinghua Hu, Daren Yu, Zongxia Xie
ANLP
2000
86views more  ANLP 2000»
13 years 8 months ago
A Finite State and Data-Oriented Method for Grapheme to Phoneme Conversion
A finite-state method, based on leftmost longestmatch replacement, is presented for segmenting words into graphemes, and for converting graphemes into phonemes. A small set of han...
Gosse Bouma