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» Learning probabilistic models of the Web
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ICML
2008
IEEE
16 years 7 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach
NIPS
2003
15 years 7 months ago
Warped Gaussian Processes
We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
WEBI
2004
Springer
15 years 11 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
CVPR
2012
IEEE
13 years 9 months ago
From Pictorial Structures to deformable structures
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connecte...
Silvia Zuffi, Oren Freifeld, Michael J. Black
ICTIR
2009
Springer
16 years 1 months ago
Time-Sensitive Language Modelling for Online Term Recurrence Prediction
We address the problem of online term recurrence prediction: for a stream of terms, at each time point predict what term is going to recur next in the stream given the term occurre...
Dell Zhang, Jinsong Lu, Robert Mao, Jian-Yun Nie