dca.py 文件源码

def get_Gt(u, gradf, t):
    # vector used for backtracking check with projected gradient descent

    u_n = u - t * gradf;
    norm_u_n = norm(u_n);

    if (norm_u_n > 1.0): # project to L2 unit ball
        u_norm = u_n / norm_u_n;
    else:
        u_norm = u_n;

    Gt = 1.0/t * (u - u_norm);

    return Gt






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##  DCA_ONE STOCH  - STOCHASTIC GRADIENT DESCENT ##
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