Adaptive diffusion kernel learning from biological networks for protein function prediction

BMC Bioinformatics

Table 1 Summary of the proposed formulations. ${DKL}_{KL}^{u}$

Algorithm	Single task	Multiple tasks	Convexity	Constraint
DKL	✓		✓	✓
DKL_KL	✓			✓
${DKL}_{KL}^{u}$	✓
mDKL		✓	✓	✓
mDKL_KL		✓		✓
${mDKL}_{KL}^{u}$		✓

These formulations are categorized in terms of the number of tasks, convexity, and whether the weights on kernels are constrained. DKLKL, DKL, and ${DKL}_{KL}^{u}$ denote formulations using the Kullback-Leibler (KL) divergence criterion, the KL divergence criterion with the log term removed and the unconstrained version for single task, respectively. A lower case m is added before each method to denote the corresponding formulations for multiple tasks.

ISSN: 1471-2105