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CORR
2010
Springer
146views Education» more  CORR 2010»
14 years 10 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
MTA
2006
173views more  MTA 2006»
14 years 9 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
VLDB
2002
ACM
126views Database» more  VLDB 2002»
14 years 9 months 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...
AI
2009
Springer
15 years 4 months ago
Grid-Enabled Adaptive Metamodeling and Active Learning for Computer Based Design
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Dirk Gorissen
KCAP
2009
ACM
15 years 4 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