Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pool-based sequential active learning with multi kernels   We study a pool-based sequential active learning (AL), in which one sample is
queried at each time from a large pool of unlabeled data according to a
selection criterion. For this framework, we propose two selection criteria,
named expected-kernel-discrepancy (EKD) and expected-kernel-loss (EKL), by
leveraging the particular structure of multiple kernel learning (MKL). Also, it
is identified that the proposed EKD and EKL successfully generalize the
concepts of popular query-by-committee (QBC) and expected-model-change (EMC),
respectively. Via experimental results with real-data sets, we verify the
effectiveness of the proposed criteria compared with the existing methods.

18
The categories of this paper are: econ
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin