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» Learning Gaussian processes from multiple tasks
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ICPR
2010
IEEE
15 years 4 months ago
Gaussian Process Learning from Order Relationships Using Expectation Propagation
A method for Gaussian process learning of a scalar function from a set of pair-wise order relationships is presented. Expectation propagation is used to obtain an approximation to...
Ruixuan Wang, Stephen James Mckenna
IJCAI
2007
15 years 1 months ago
WiFi-SLAM Using Gaussian Process Latent Variable Models
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor l...
Brian Ferris, Dieter Fox, Neil D. Lawrence
DSMML
2004
Springer
15 years 5 months ago
Extensions of the Informative Vector Machine
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
ICML
2007
IEEE
16 years 14 days ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu
131
Voted
CVPR
2012
IEEE
13 years 2 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu