Learning with Target Prior

no code implementations • NeurIPS 2012 • Zuoguan Wang, Siwei Lyu, Gerwin Schalk, Qiang Ji

In this work, we describe a new learning scheme for parametric learning, in which the target variables $\y$ can be modeled with a prior model $p(\y)$ and the relations between data and target variables are estimated through $p(\y)$ and a set of uncorresponded data $\x$ in training.

Pose Estimation