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ACL
2010
15 years 20 days ago
An Active Learning Approach to Finding Related Terms
We present a novel system that helps nonexperts find sets of similar words. The user begins by specifying one or more seed words. The system then iteratively suggests a series of ...
David Vickrey, Oscar Kipersztok, Daphne Koller
139
Voted
COLING
2010
14 years 9 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn
121
Voted
NIPS
2004
15 years 4 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore
111
Voted
ICML
2003
IEEE
16 years 3 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
131
Voted
TRECVID
2008
15 years 4 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...