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ICML
2007
IEEE
14 years 10 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ICML
2007
IEEE
14 years 10 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
IROS
2008
IEEE
144views Robotics» more  IROS 2008»
14 years 3 months ago
Learning nonparametric policies by imitation
— A long cherished goal in artificial intelligence has been the ability to endow a robot with the capacity to learn and generalize skills from watching a human teacher. Such an ...
David B. Grimes, Rajesh P. N. Rao
CVPR
2010
IEEE
14 years 2 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia
SAC
2005
ACM
14 years 2 months ago
Privacy preserving learning in negotiation
Machine learning techniques are widely used in negotiation systems. To get more accurate and satisfactory learning results, negotiation parties have the desire to employ learning ...
Sheng Zhang, Fillia Makedon