Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Partitioning Data on Features or Samples in Communication-Efficient
  Distributed Optimization?   In this paper we study the effect of the way that the data is partitioned in
distributed optimization. The original DiSCO algorithm [Communication-Efficient
Distributed Optimization of Self-Concordant Empirical Loss, Yuchen Zhang and
Lin Xiao, 2015] partitions the input data based on samples. We describe how the
original algorithm has to be modified to allow partitioning on features and
show its efficiency both in theory and also in practice.

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The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: hep-ph
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The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
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The categories of this paper are: hep-th
3
The categories of this paper are: physics
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The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom