Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Kernel transfer over multiple views for missing data completion   We consider the kernel completion problem with the presence of multiple views
in the data. In this context the data samples can be fully missing in some
views, creating missing columns and rows to the kernel matrices that are
calculated individually for each view. We propose to solve the problem of
completing the kernel matrices by transferring the features of the other views
to represent the view under consideration. We align the known part of the
kernel matrix with a new kernel built from the features of the other views. We
are thus able to find generalizable structures in the kernel under completion,
and represent it accurately. Its missing values can be predicted with the data
available in other views. We illustrate the benefits of our approach with
simulated data and multivariate digits dataset, as well as with real biological
datasets from studies of pattern formation in early \textit{Drosophila
melanogaster} embryogenesis.

17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat