Efficient l₁-norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method. Kim, E., Lee, M., Choi, C., Kwak, N., & Oh, S. IEEE Transactions on Neural Networks and Learning Systems, 26:237 - 251, IEEE, 2014. bibtex @Article{Kim_2014_16158,
author = {Kim, E. and Lee, M. and Choi, C.-H. and Kwak, N. and Oh, S.},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
pages = {237 - 251},
publisher = {IEEE},
title = {Efficient l₁-norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method},
volume = {26},
year = {2014},
title_with_no_special_chars = {Efficient lNormBased LowRank Matrix Approximations for LargeScale Problems Using Alternating Rectified Gradient Method}
}
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