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ACL
1996
13 years 9 months ago
Minimizing Manual Annotation Cost in Supervised Training from Corpora
Corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. This paper investigates methods for ...
Sean P. Engelson, Ido Dagan
AAAI
2011
12 years 8 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
SP
2008
IEEE
176views Security Privacy» more  SP 2008»
14 years 2 months ago
Casting out Demons: Sanitizing Training Data for Anomaly Sensors
The efficacy of Anomaly Detection (AD) sensors depends heavily on the quality of the data used to train them. Artificial or contrived training data may not provide a realistic v...
Gabriela F. Cretu, Angelos Stavrou, Michael E. Loc...
INTERSPEECH
2010
13 years 2 months ago
Learning from human errors: prediction of phoneme confusions based on modified ASR training
In an attempt to improve models of human perception, the recognition of phonemes in nonsense utterances was predicted with automatic speech recognition (ASR) in order to analyze i...
Bernd T. Meyer, Birger Kollmeier
MM
2004
ACM
178views Multimedia» more  MM 2004»
14 years 1 months ago
A bootstrapping framework for annotating and retrieving WWW images
Most current image retrieval systems and commercial search engines use mainly text annotations to index and retrieve WWW images. This research explores the use of machine learning...
HuaMin Feng, Rui Shi, Tat-Seng Chua