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NAACL
2003
15 years 3 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
VL
2010
IEEE
160views Visual Languages» more  VL 2010»
15 years 25 days ago
Toward End-User Debugging of Machine-Learned Classifiers
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a generat...
Todd Kulesza
LREC
2008
104views Education» more  LREC 2008»
15 years 3 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...
TIP
2008
169views more  TIP 2008»
15 years 2 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
229
Voted
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
15 years 14 days ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...