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» Improving Web Data Annotations with Spreading Activation
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EMNLP
2008
13 years 10 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
ACL
2010
13 years 6 months ago
Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation
We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...
Michael Bloodgood, Chris Callison-Burch
ICASSP
2008
IEEE
14 years 2 months ago
Learning with noisy supervision for Spoken Language Understanding
Data-driven Spoken Language Understanding (SLU) systems need semantically annotated data which are expensive, time consuming and prone to human errors. Active learning has been su...
Christian Raymond, G. Riccardfi
CVPR
2009
IEEE
15 years 3 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
ICAC
2008
IEEE
14 years 2 months ago
Guided Problem Diagnosis through Active Learning
There is widespread interest today in developing tools that can diagnose the cause of a system failure accurately and efficiently based on monitoring data collected from the syst...
Songyun Duan, Shivnath Babu