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90
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NIPS
2001
15 years 2 months ago
Active Learning in the Drug Discovery Process
We investigate the following data mining problem from Computational Chemistry: From a large data set of compounds, find those that bind to a target molecule in as few iterations o...
Manfred K. Warmuth, Gunnar Rätsch, Michael Ma...
100
Voted
CORR
2010
Springer
146views Education» more  CORR 2010»
15 years 1 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
99
Voted
VLDB
2002
ACM
126views Database» more  VLDB 2002»
15 years 23 days ago
ALIAS: An Active Learning led Interactive Deduplication System
Deduplication, a key operation in integrating data from multiple sources, is a time-consuming, labor-intensive and domainspecific operation. We present our design of alias that us...
Sunita Sarawagi, Anuradha Bhamidipaty, Alok Kirpal...
123
Voted
KCAP
2009
ACM
15 years 7 months ago
Reducing class imbalance during active learning for named entity annotation
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Katrin Tomanek, Udo Hahn
90
Voted
NAACL
2004
15 years 2 months ago
Ensemble-based Active Learning for Parse Selection
Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to ...
Miles Osborne, Jason Baldridge