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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