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ECML
2006
Springer
13 years 9 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
ITS
2004
Springer
81views Multimedia» more  ITS 2004»
13 years 11 months ago
Towards Adaptive Generation of Faded Examples
Abstract. Faded examples have been investigated in pedagogical psychology. The experiments suggest that a learner can benefit from faded examples. For these experiments a few exam...
Erica Melis, Georgi Goguadze
IEAAIE
2001
Springer
13 years 10 months ago
Selecting a Relevant Set of Examples to Learn IE-Rules
The growing availability of online text has lead to an increase in the use of automatic knowledge acquisition approaches from textual data, as in Information Extraction (IE). Some ...
Jordi Turmo, Horacio Rodríguez
NIPS
2007
13 years 7 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 3 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer