… directions in the image before further factorization can be applied. This … to factorization, which
introduces directional uncertainty into … matrices which represent the uncertainty in the data. …

… of directional uncertainty. In particular, we show that unlike other SVD-based factorization
algorithms, our method does not degrade with increase in directionality of uncertainty, even in …

Multibody factorization algorithms give an elegant and simple solution to the problem of …
In this paper we present a multibody factorization algorithm that can handle arbitrary noise …

… Our uncertainty formulation provides a natural method for modeling line segments, thus …
the factorization algorithm in Section 2. Then, in Section 3, we describe our uncertainty model …

… In this paper we extend the notion of factorization with uncertainty to multiple (rigid or non-…
segmentation we introduce directional uncertainty into the multi-body factorization process. …

… Under these conditions, most existing factorization algorithms fail while human perception
is … factorization. This allows us to easily handle missing data and measurement uncertainty …

… -norm-based matrix factorization method which relies on side information in the form of an
estimate of the uncertainty of each rating. A rating with a higher uncertainty is considered more …

… On a chemical brain imaging data set, we show that this improves interpretability by providing
uncertainty estimates. We discuss how the Gibbs sampler can be used for model order …

… We have created a new algorithm, least squares non-negative matrix factorization, LS-NMF,
which integrates uncertainty measurements of gene expression data into NMF updating …

… and factorization scale uncertainties of Higgs-pair production via gluon fusion with the novel
uncertainties … Moreover, we address the uncertainties related to the top-mass definition for …