@InProceedings{RaWiKrHa10,
Title = {Ungrounded Independent Non-Negative Factor Analysis},
Author = {Raj, Bhiksha and Wilson, {Kevin W.} and Krueger, Alexander and Haeb-Umbach, Reinhold},
Booktitle = {Interspeech 2010},
Year = {2010},
Abstract = {We describe an algorithm that performs regularized non-negative matrix factorization (NMF) to find independent components in non-negative data. Previous techniques proposed for this purpose require the data to be grounded, with support that goes down to 0 along each dimension. In our work, this requirement is eliminated. Based on it, we present a technique to find a low-dimensional decomposition of spectrograms by casting it as a problem of discovering independent non-negative components from it. The algorithm itself is implemented as regularized non-negative matrix factorization (NMF). Unlike other ICA algorithms, this algorithm computes the mixing matrix rather than an unmixing matrix. This algorithm provides a better decomposition than standard NMF when the underlying sources are independent. It makes better use of additional observation streams than previous non-negative ICA algorithms.},
Url = {https://groups.uni-paderborn.de/nt/pubs/2010/RaWiKrHa10.pdf}
}