PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Mikkel Schmidt

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Number of EPrints submitted by this user: 15

Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation
Mikkel Schmidt and Morten Mørup
Independent Component Analysis and Blind Signal Separation, 6th International Conference, ICA 2006, Charleston, SC, USA, March 5-8, 2006, Proceedings Volume 3889, pp. 700-707, 2006.

Single-Channel Speech Separation using Sparse Non-Negative Matrix Factorization
Mikkel Schmidt and Rasmus Olsson
In: Interspeech 2006, Pittsburgh, PA, USA(2006).

Wind Noise Reduction using Non-negative Sparse Coding
Mikkel N. Schmidt, Jan Larsen and Fu-Tien Hsiao
In: Machine Learning for Signal Processing, IEEE Workshop on (MLSP), 2007(2007).

Linear Regression on Sparse Features for Single-Channel Speech Separation
Mikkel N. Schmidt and Rasmus K. Olsson
In: Applications of Signal Processing to Audio and Acoustics, IEEE Workshop on (WASPAA), 2007(2007).

Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition
Mikkel N. Schmidt and Jan Larsen
In: Machine Learning for Signal Processing, IEEE Workshop on (MLSP), 2008(2008).

Structured non-negative matrix factorization with sparsity patterns
Hans Laurberg, Mikkel N. Schmidt, Mads G. Christensen and Søren Holdt Jensen
In: Hans Laurberg, Mikkel N. Schmidt, Mads G. Christensen, and Søren H. Jensen Structured non-negative matrix factorization with sparsity patterns Signals, Systems and Computers, Asilomar Conference on, 2008(2008).

Bayesian nonnegative matrix factorization with volume prior for unmixing of hyperspectral images
Morten Arngren, Mikkel N. Schmidt and Jan Larsen
In: Bayesian nonnegative matrix factorization with volume prior for unmixing of hyperspectral images(2009).

Bayesian non-negative matrix factorization
Mikkel N. Schmidt, Ole Winter and Lars Kai Hansen
In: Independent Component Analysis and Signal Separation, International Conference on, 2009(2009).

Function factorization using warped Gaussian processes
Mikkel N. Schmidt
In: Machine Learning, International Conference on (ICML), 2009(2009).

Probabilistic non-negative tensor factorization using Markov chain Monte Carlo
Mikkel N. Schmidt and Shakir Mohamed
In: European Signal Processing Conference (EUSIPCO), 2009(2009).

Linearly constrained Bayesian matrix factorization for blind source separation
Mikkel N. Schmidt
In: Neural Information Processing Systems, Advances in (NIPS), 2009(2009).

Non-negative matrix factorization with Gaussian process priors
Mikkel N. Schmidt and Hans Laurberg
Computational Intelligence and Neuroscience 2008.

Infinite non-negative matrix factorization
Mikkel N. Schmidt and Morten Mørup
In: EUSIPCO(2010).

Infinite multiple membership relational modeling for complex networks
Mikkel N. Schmidt, Morten Mørup and Lars Kai Hansen
In: Machine Learning for Signal Processing, IEEE International Workshop on (MLSP)(2011).

Transformation invariant sparse coding
Morten Mørup and Mikkel N. Schmidt
In: Machine Learning for Signal Processing, IEEE International Workshop on (MLSP)(2011).