Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Distributed Cubic-Regularized Newton Method for Smooth Convex
  Optimization over Networks   We propose a distributed, cubic-regularized Newton method for large-scale
convex optimization over networks. The proposed method requires only local
computations and communications and is suitable for federated learning
applications over arbitrary network topologies. We show a $O(k^{{-}3})$
convergence rate when the cost function is convex with Lipschitz gradient and
Hessian, with $k$ being the number of iterations. We further provide
network-dependent bounds for the communication required in each step of the
algorithm. We provide numerical experiments that validate our theoretical
results.

31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
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The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph