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» Learning with Knowledge from Multiple Experts
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ASPLOS
2008
ACM
14 years 11 months ago
Learning from mistakes: a comprehensive study on real world concurrency bug characteristics
The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Addressing this challenge requires adva...
Shan Lu, Soyeon Park, Eunsoo Seo, Yuanyuan Zhou
89
Voted
ICRA
2002
IEEE
128views Robotics» more  ICRA 2002»
15 years 2 months ago
Generation of a Task Model by Integrating Multiple Observations of Human Demonstrations
This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
14 years 8 months ago
Searching for objects: Combining multiple cues to object locations using a maximum entropy model
— In this paper, we consider the problem of how background knowledge about usual object arrangements can be utilized by a mobile robot to more efficiently find an object in an ...
Dominik Joho, Wolfram Burgard
88
Voted
IJAR
2007
130views more  IJAR 2007»
14 years 9 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
AAAI
1996
14 years 11 months ago
Post-Analysis of Learned Rules
Rule induction research implicitly assumes that after producing the rules from a dataset, these rules will be used directly by an expert system or a human user. In real-life appli...
Bing Liu, Wynne Hsu