Description Usage Arguments Value
Solve the projected dual ascent problem with fixed weights and adaptive step size
1 | dual_ascent_adapt(X, Phi, weights, Lambda0, maxiter, eps, nv0, trace)
|
X |
the data, with the columns being units, the rows being features |
Phi |
the edge incidence matrix, defined as Phi_li = 1 if(l_1 == i); -1 if(l_2 == i); 0 otherwise |
weights |
the non-zero weights in a vector |
Lambda0 |
the initial guess of Lambda |
maxiter |
maximum iterations |
eps |
the duality gap tolerence |
trace |
whether save the primal and dual values of every iteration |
nv |
initial step size |
a list including U, V, Lambda and number of iterations to convergence
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