An SMO algorithm in Fan et al., JMLR 6(2005), p. 1889--1918 Solves: min 0.5(\alpha^T Q \alpha) + p^T \alpha y^T \alpha = \delta y_i = +1 or -1 0 <= alpha_i <= Cp for y_i = 1 0 <= alpha_i <= Cn for y_i = -1 Given: Q, p, y, Cp, Cn, and an initial feasible point \alpha l is the size of vectors and matrices eps is the stopping tolerance solution will be put in \alpha, objective value will be put
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