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Generalised Coupled Tensor Factorisation
"... We derive algorithms for generalised tensor factorisation (GTF) by building upon the wellestablished theory of Generalised Linear Models. Our algorithms are general in the sense that we can compute arbitrary factorisations in a message passing framework, derived for a broad class of exponential fam ..."
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We derive algorithms for generalised tensor factorisation (GTF) by building upon the wellestablished theory of Generalised Linear Models. Our algorithms are general in the sense that we can compute arbitrary factorisations in a message passing framework, derived for a broad class of exponential
prediction via generalized coupled tensor factorisation
 in ECML/PKDDWorkshop on Collective Learning and Inference on Structured Data
, 2012
"... Abstract. This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction using coupled analysis of relational datasets represented as heterogeneous data, i.e., datasets in the form of ..."
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Cited by 4 (1 self)
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of matrices and higherorder tensors. We propose to use an approach based on probabilistic interpretation of tensor factorisation models, i.e., Generalised Coupled Tensor Factorisation, which can simultaneously fit a large class of tensor models to higherorder tensors/matrices with common latent factors
Shifted 2D Nonnegative Tensor Factorisation
"... ... developed as a means of separating harmonic instruments from single channel mixtures. This technique uses a model which is convolutive in both time and frequency, and so can capture instruments which have both timevarying spectra and timevarying fundamental frequencies simultaneously. However, ..."
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Cited by 5 (2 self)
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, in many cases two or more channels are available, in which case it would be advantageous to have a multichannel version of the algorithm. To this end, a shifted 2D Nonnegative Tensor Factorisation algorithm is derived, which extends Nonnegative Matrix Factor 2D Deconvolution to the multichannel case
Nonnegative tensor factorisation for sound source separation
 IN: PROCEEDINGS OF IRISH SIGNALS AND SYSTEMS CONFERENCE
, 2005
"... ... is introduced which extends current matrix factorisation techniques to deal with tensors. The effectiveness of the algorithm is then demonstrated through tests on synthetic data. The algorithm is then employed as a means of performing sound source separation on two channel mixtures, and the sepa ..."
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Cited by 28 (2 self)
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... is introduced which extends current matrix factorisation techniques to deal with tensors. The effectiveness of the algorithm is then demonstrated through tests on synthetic data. The algorithm is then employed as a means of performing sound source separation on two channel mixtures
USING TENSOR FACTORISATION MODELS TO SEPARATE DRUMS FROM POLYPHONIC MUSIC
"... This paper describes the use of Nonnegative Tensor Factorisation models for the separation of drums from polyphonic audio. Improved separation of the drums is achieved through the incorporation of Gamma Chain priors into the Nonnegative Tensor Factorisation framework. In contrast to many previo ..."
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Cited by 5 (1 self)
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This paper describes the use of Nonnegative Tensor Factorisation models for the separation of drums from polyphonic audio. Improved separation of the drums is achieved through the incorporation of Gamma Chain priors into the Nonnegative Tensor Factorisation framework. In contrast to many
User assisted separation using tensor factorisations
 in 20th European Signal Processing Conference (EUSIPCO 2012
, 2012
"... This Conference Paper is brought to you for free and open access by the ..."
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Cited by 1 (0 self)
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This Conference Paper is brought to you for free and open access by the
SCORE GUIDED AUDIO RESTORATION VIA GENERALISED COUPLED TENSOR FACTORISATION
"... Generalised coupled tensor factorisation is a recently proposed algorithmic framework for simultaneously estimating tensor factorisation models where several observed tensors can share a set of latent factors. This paper proposes a model in this framework for coupled factorisation of piano spectrogr ..."
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Cited by 5 (1 self)
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Generalised coupled tensor factorisation is a recently proposed algorithmic framework for simultaneously estimating tensor factorisation models where several observed tensors can share a set of latent factors. This paper proposes a model in this framework for coupled factorisation of piano
Musical Source Separation using Generalised NonNegative Tensor Factorisation models
"... A shiftinvariant nonnegative tensor factorisation algorithm for musical source separation is proposed which generalises previous work by allowing each source to have its own parameters rather a fixed set of parameters for all sources. This allows independent control of the number of allowable note ..."
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Cited by 2 (2 self)
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A shiftinvariant nonnegative tensor factorisation algorithm for musical source separation is proposed which generalises previous work by allowing each source to have its own parameters rather a fixed set of parameters for all sources. This allows independent control of the number of allowable
Sound Source Separation using Shifted Nonnegative Tensor Factorisation
 Proceedings on the IEE Conference on Audio and Speech Signal Processing (ICASSP
, 2006
"... Recently, shifted Nonnegative Matrix Factorisation was developed as a means of separating harmonic instruments from single channel mixtures. However, in many cases two or more channels are available, in which case it would be advantageous to have a multichannel version of the algorithm. To this end ..."
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Cited by 15 (0 self)
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. To this end, a shifted Nonnegative Tensor Factorisation algorithm is derived, which extends shifted Nonnegative Matrix Factorisation to the multichannel case. The use of this algorithm for multichannel sound source separation of harmonic instruments is demonstrated. Further, it is shown that the algorithm
Extended Nonnegative Tensor Factorisation models for Musical Sound Source Separation
"... Recently, shift invariant tensor factorisation algorithms have been proposed for the purposes of sound source separation of pitched musical instruments. However, existing algorithms require the use of logfrequency spectrograms to allow shift invariance in frequency which causes problems when attemp ..."
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Recently, shift invariant tensor factorisation algorithms have been proposed for the purposes of sound source separation of pitched musical instruments. However, existing algorithms require the use of logfrequency spectrograms to allow shift invariance in frequency which causes problems when
Results 1  10
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39