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» Active Learning by Labeling Features
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109
Voted
ICML
2010
IEEE
15 years 3 months ago
Active Risk Estimation
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
135
Voted
DIAL
2004
IEEE
164views Image Analysis» more  DIAL 2004»
15 years 6 months ago
A Dynamic Feature Generation System for Automated Metadata Extraction in Preservation of Digital Materials
Obsolescence in storage media and the hardware and software for access and use can render old electronic files inaccessible and unusable. Therefore, the long-term preservation of ...
Song Mao, Jongwoo Kim, George R. Thoma
168
Voted
ICOST
2011
Springer
14 years 6 months ago
Using Association Rule Mining to Discover Temporal Relations of Daily Activities
The increasing aging population has inspired many machine learning researchers to find innovative solutions for assisted living. A problem often encountered in assisted living set...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook
87
Voted
AAAI
1998
15 years 4 months ago
Feature Generation for Sequence Categorization
The problem of sequence categorization is to generalize from a corpus of labeled sequences procedures for accurately labeling future unlabeled sequences. The choice of representat...
Daniel Kudenko, Haym Hirsh
131
Voted
NIPS
1997
15 years 4 months ago
A Framework for Multiple-Instance Learning
Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many ins...
Oded Maron, Tomás Lozano-Pérez