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EMNLP
2009
15 years 4 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
ICMLA
2009
15 years 4 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
151
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ICML
2008
IEEE
16 years 7 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
SEMCO
2007
IEEE
16 years 29 days ago
Learning by Reading by Learning to Read
Knowledge-based natural language processing systems learn by reading, i.e., they process texts to extract knowledge. The performance of these systems crucially depends on knowledg...
Sergei Nirenburg, Tim Oates, Jesse English
LREC
2008
78views Education» more  LREC 2008»
15 years 8 months ago
Approximating Learning Curves for Active-Learning-Driven Annotation
Active learning (AL) is getting more and more popular as a methodology to considerably reduce the annotation effort when building training material for statistical learning method...
Katrin Tomanek, Udo Hahn