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ACL
2009
15 years 4 months ago
Semi-Supervised Active Learning for Sequence Labeling
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned a...
Katrin Tomanek, Udo Hahn
ICML
1996
IEEE
16 years 7 months ago
Passive Distance Learning for Robot Navigation
Autonomous mobile robots need good models of their environment, sensors and actuators to navigate reliably and efficiently. While this information can be supplied by humans, or le...
Sven Koenig, Reid G. Simmons
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
15 years 4 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
16 years 20 days ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
TKDE
2008
148views more  TKDE 2008»
15 years 6 months ago
Semisupervised Clustering with Metric Learning using Relative Comparisons
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
Nimit Kumar, Krishna Kummamuru