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» Learning the Structure of Deep Sparse Graphical Models
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JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
ICML
2007
IEEE
14 years 9 months ago
Incremental Bayesian networks for structure prediction
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Ivan Titov, James Henderson
UAI
1998
13 years 10 months ago
Learning Mixtures of DAG Models
We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
WEBI
2004
Springer
14 years 2 months ago
Adaptation and Personalization in Web-based Learning Support Systems
In order to achieve optimal efficiency in a learning process, individual learner needs his/her own personalized assistance. For a web-based open and dynamic learning environment, ...
Lisa Fan
ICRA
2008
IEEE
206views Robotics» more  ICRA 2008»
14 years 3 months ago
Memory-based learning for visual odometry
Abstract— We present and examine a technique for estimating the ego-motion of a mobile robot using memory-based learning and a monocular camera. Unlike other approaches that rely...
Richard Roberts, Hai Nguyen, Niyant Krishnamurthi,...