Description Usage Arguments Value

Solve the projected dual ascent problem with fixed weights and adaptive step size and back-tracking

1 | ```
dual_ascent_fasta(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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