Asymptotic convergence of an SMO algorithm without any assumptions
Chih‐Jen Lin · IEEE Transactions on Neural Networks · 2002
The asymptotic convergence of C.-J. Lin (2001) can be applied to a modified SMO (sequential minimal optimization) algorithm by S.S. Keerthi et al. (2001) with some assumptions. The author shows that for this algorithm those assumptions are not necessary.