Algorithms, Initializations, and Convergence for t
2016-08-23
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It is well-known that good initializations can improve the speed and accuracy of the solutions of
many nonnegative matrix factorization (NMF) algorithms [56]. Many NMF algorithms are sensitive
with respect to the initialization of W or H or both. This is especially true of algorithms of the
alternating least squares (ALS) type [55], including the two new ALS algorithms that we present in this
paper. We compare the results of six initialization procedures (two standard and four new) on our ALS
algorithms. Lastly, we discuss the practical issue of choosing an appropriate convergence criterion.
many nonnegative matrix factorization (NMF) algorithms [56]. Many NMF algorithms are sensitive
with respect to the initialization of W or H or both. This is especially true of algorithms of the
alternating least squares (ALS) type [55], including the two new ALS algorithms that we present in this
paper. We compare the results of six initialization procedures (two standard and four new) on our ALS
algorithms. Lastly, we discuss the practical issue of choosing an appropriate convergence criterion.
算法
矩阵
分解
初始化
收敛
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