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ICML
2010
IEEE
15 years 7 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
CIKM
2007
Springer
16 years 23 days ago
Developing learning strategies for topic-based summarization
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
Ouyang You, Sujian Li, Wenjie Li
ICRA
2009
IEEE
170views Robotics» more  ICRA 2009»
16 years 1 months ago
Imitation learning with generalized task descriptions
— In this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. Motion capture data is recorded in ...
Clemens Eppner, Jürgen Sturm, Maren Bennewitz...
ESAS
2006
Springer
15 years 10 months ago
Dynamics of Learning Algorithms for the On-Demand Secure Byzantine Routing Protocol
We investigate the performance of of several protocol enhancements to the On-Demand Secure Byzantine Routing (ODSBR) [3] protocol in the presence of various Byzantine Attack models...
Baruch Awerbuch, Robert G. Cole, Reza Curtmola, Da...
ICASSP
2008
IEEE
16 years 1 months ago
An iterative unsupervised learning method for information distillation
Information distillation techniques are used to analyze and interpret large volumes of speech and text archives in multiple languages and produce structured information of interes...
Kamand Kamangar, Dilek Hakkani-Tür, Gökh...