Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Communication-Efficient Distributed Online Learning with Kernels   We propose an efficient distributed online learning protocol for low-latency
real-time services. It extends a previously presented protocol to kernelized
online learners that represent their models by a support vector expansion.
While such learners often achieve higher predictive performance than their
linear counterparts, communicating the support vector expansions becomes
inefficient for large numbers of support vectors. The proposed extension allows
for a larger class of online learning algorithms---including those alleviating
the problem above through model compression. In addition, we characterize the
quality of the proposed protocol by introducing a novel criterion that requires
the communication to be bounded by the loss suffered.

23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex