Sciweavers

Share
ICML
2007
IEEE

Robust multi-task learning with t-processes

10 years 2 months 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. We introduce a robust framework for Bayesian multitask learning, t-processes (TP), which are a generalization of Gaussian processes (GP) for multi-task learning. TP allows the system to effectively distinguish good tasks from noisy or outlier tasks. Experiments show that TP not only improves overall system performance, but can also serve as an indicator for the "informativeness" of different tasks.
Shipeng Yu, Volker Tresp, Kai Yu
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2007
Where ICML
Authors Shipeng Yu, Volker Tresp, Kai Yu
Comments (0)
books