Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contrastive Multivariate Singular Spectrum Analysis   We introduce Contrastive Multivariate Singular Spectrum Analysis, a novel
unsupervised method for dimensionality reduction and signal decomposition of
time series data. By utilizing an appropriate background dataset, the method
transforms a target time series dataset in a way that evinces the sub-signals
that are enhanced in the target dataset, as opposed to only those that account
for the greatest variance. This shifts the goal from finding signals that
explain the most variance to signals that matter the most to the analyst. We
demonstrate our method on an illustrative synthetic example, as well as show
the utility of our method in the downstream clustering of electrocardiogram
signals from the public MHEALTH dataset.

26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th