Introduction Relational Kernel Learning o Kernel function: To characterize the similarity between data instances: K(xi,xj) e.g.,K(cat,tiger)>K(cat,elephant) Positive semidefiniteness (p.s.d.) o Kernel learning: To learn an appropriate kernel matrix or kernel function for a kernel-based learning method. o Relational kernel learning (RKL): To learn an appropriate kernel matrix or kernel function for relational data by incorporating relational information between instances into the learning process. 4口40+4立4至，三)及0 Li,Zhang and Yeung (CSE,HKUST) LWP A1 STATS20094/23Introduction Relational Kernel Learning Kernel function: To characterize the similarity between data instances: K(xi , xj) e.g., K(cat,tiger) > K(cat, elephant) Positive semidefiniteness (p.s.d.) Kernel learning: To learn an appropriate kernel matrix or kernel function for a kernel-based learning method. Relational kernel learning (RKL): To learn an appropriate kernel matrix or kernel function for relational data by incorporating relational information between instances into the learning process. Li, Zhang and Yeung (CSE, HKUST) LWP AISTATS 2009 4 / 23