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Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the… (More)

Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be… (More)

The dual formulation of the support vector machine (SVM) objective function is an instance of a nonnegative quadratic programming problem. We reformulate the SVM objective function as a matrix… (More)

Have you ever wanted to multiply an n × d matrix X , with n d, on the left by an m × n matrix G̃ of i.i.d. Gaussian random variables, but could not afford to do it because it was too slow? In this… (More)

We present multiplicative updates for solving hard and soft margin support vector machines (SVM) with non-negative kernels. They follow as a natural extension of the updates for non-negative matrix… (More)

- Vamsi K. Potluru
- AAAI
- 2012

The Nonnegative Least Squares (NNLS) formulation arises in many important regression problems. We present a novel coordinate descent method which differs from previous approaches in that we do not… (More)

- Rogers F. Silva, Eduardo Castro, +5 authors Vince D. Calhoun
- 2014 IEEE International Workshop on Machine…
- 2014

For the 24th Machine Learning for Signal Processing competition, participants were asked to automatically diagnose schizophrenia using multimodal features derived from MRI scans. The objective of the… (More)

- Vince D. Calhoun, Vamsi K. Potluru, +5 authors Tülay Adalı
- PloS one
- 2013

A recent paper by Daubechies et al. claims that two independent component analysis (ICA) algorithms, Infomax and FastICA, which are widely used for functional magnetic resonance imaging (fMRI)… (More)

- Vamsi K. Potluru, Vince D. Calhoun
- 2008 IEEE International Symposium on Circuits and…
- 2008

Non-negative matrix factorization (NMF) has increasingly been used as a tool in signal processing in the last couple of years. NMF, like independent component analysis (ICA) is useful for decomposing… (More)

The growth of data sharing initiatives in neuroscience and genomics [14, 16, 19, 25] represents an exciting opportunity to confront the “small N” problem plaguing contemporary studies [20]. When… (More)