Plumbley, M.D. "Conditions for non-negative independent component analysis". In IEEE Signal Processing Letters, 9(6), pp177-180, (2002). Home/Search Document Details and Download
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Probabilistic Models of Early Vision - Hoyer (Correct)
.... a neurobiological context by Lee and Seung [81] calling it non negative matrix factorization) who also developed e#cient algorithms for solving the problem [81, 82] In the context of ICA, non negativity constraints (on A, s, or both) have recently been considered by several authors, see e.g. [97, 106, 114, 117, 118]. The main contributions of Publication 4 were the application of non negativity constraints in the sparse coding framework [110, 111] and the extension of the algorithm proposed in [82] to this case. 9.3 Learning receptive fields In Publication 5, the algorithm proposed in Publication 4 was ....
M. Plumbley, "Conditions for non-negative independent component analysis," IEEE Signal Processing Letters, vol. 9, no. 6, pp. 177--180, 2002.
Probabilistic Models of Early Vision - Hoyer (2002) (Correct)
.... a neurobiological context by Lee and Seung [81] calling it non negative matrix factorization) who also developed e#cient algorithms for solving the problem [81, 82] In the context of ICA, non negativity constraints (on A, s, or both) have recently been considered by several authors, see e.g. [97, 106, 114, 117, 118]. The main contributions of Publication 4 were the application of non negativity constraints in the sparse coding framework [110, 111] and the extension of the algorithm proposed in [82] to this case. 9.3 Learning receptive fields In Publication 5, the algorithm proposed in Publication 4 was ....
M. Plumbley, "Conditions for non-negative independent component analysis," IEEE Signal Processing Letters, vol. 9, no. 6, pp. 177--180, 2002.
Optimization using Fourier Expansion over a Geodesic For.. - Plumbley (2004) Self-citation (Plumbley) (Correct)
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Plumbley, M.D.: Conditions for nonnegative independent component analysis. IEEE Signal Processing Letters 9 (2002) 177--180
Blind Separation Of Positive Sources Using Non-Negative PCA - Oja, Plumbley (2003) (1 citation) Self-citation (Plumbley) (Correct)
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M. D. Plumbley, "Conditions for nonnegative independent component analysis," IEEE Signal Processing Letters, vol. 9, no. 6, pp. 177 --180, June 2002.
Algorithms for Non-Negative Independent Component Analysis - Plumbley (2002) (2 citations) Self-citation (Plumbley) (Correct)
.... to show that the dual constraints of non negativity and independence of sources lead to the conclusions that, under certain reasonable assumptions, source separation of pre whitened data can be achieved by finding an orthonormal matrix that minimizes reconstruction error from rectified outputs [15]. In the next section we shall see that this leads naturally to a form of nonlinear PCA algorithm, and leads on to other algorithms operating directly in the manifold of orthonormal matrices. III. NON NEGATIVE ICA USING NONLINEAR PCA A. Pre whitening The ICA problem can often be simplified if ....
.... search for an extremum of a contrast function, which are expressed as either higher order cumulants or non linear cross terms between outputs: for a discussion, see e.g. 3] 4] ALGORITHMS FOR NON NEGATIVE INDEPENDENT COMPONENT ANALYSIS We considered the case of our non negative ICA problem in [15]. Suppose that the vector of sources s is an n dimensional random vector of real valued, non negative sources. Suppose further that the components of s are well grounded, meaning that they have a non zero pdf in the positive neighbourhood of s = 0, i.e. for any 5 0 we have Pr(s 5) 0. Then ....
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M.D. Plumbley, "Conditions for non-negative independent component analysis," IEEE Signal Processing Letters, 2002, In Press.
Non-Negative Matrix Factorization for Polyphonic Music.. - Smaragdis, Brown (2003) (4 citations) (Correct)
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Plumbley, M.D. "Conditions for non-negative independent component analysis". In IEEE Signal Processing Letters, 9(6), pp177-180, (2002).
Non-Negative Matrix Factorization for Polyphonic Music.. - Smaragdis, Brown (2003) (4 citations) (Correct)
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Plumbley, M.D. "Conditions for non-negative independent component analysis". In IEEE Signal Processing Letters, 9(6), pp177-180, (2002).
When Does Non-Negative Matrix Factorization Give Correct.. - Donoho, Stodden (2003) (7 citations) (Correct)
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M. Plumbley. Conditions for nonnegative independent components analysis. Signal Processing Letters, IEEE, 9(6):177-180, 2002.
Patrik O. Hoyer - Neural Networks Research (Correct)
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M. Plumbley, "Conditions for non-negative independent component analysis," IEEE Signal Processing Letters, 2002, in press.
Patrik O. Hoyer - Neural Networks Research (Correct)
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M. Plumbley, "Conditions for non-negative independent component analysis," IEEE Signal Processing Letters, 2002, in press.
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