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» On Issues of Instance Selection
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IROS
2007
IEEE
123views Robotics» more  IROS 2007»
14 years 4 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura
CVPR
2010
IEEE
14 years 6 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
CVPR
2011
IEEE
13 years 7 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...
MONET
2006
89views more  MONET 2006»
13 years 10 months ago
Sensing-based opportunistic channel access
Enabled by regulatory initiatives and advanced radio technology, more flexible opportunistic spectrum access has great potential to alleviate the spectrum scarcity. In this paper,...
Xin Liu, Sai Shankar N.
ESWS
2008
Springer
13 years 11 months ago
Numeric reasoning in the Semantic Web
Abstract. The Semantic Web is an effort by the W3C to enable integration and sharing of information across different applications and organizations using annotations by means of on...
Chimène Fankam, Stéphane Jean, Guy P...