Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Asynchronous Convex Consensus in the Presence of Crash Faults   This paper defines a new consensus problem, convex consensus. Similar to
vector consensus [13, 20, 19], the input at each process is a d-dimensional
vector of reals (or, equivalently, a point in the d-dimensional Euclidean
space). However, for convex consensus, the output at each process is a convex
polytope contained within the convex hull of the inputs at the fault-free
processes. We explore the convex consensus problem under crash faults with
incorrect inputs, and present an asynchronous approximate convex consensus
algorithm with optimal fault tolerance that reaches consensus on an optimal
output polytope. Convex consensus can be used to solve other related problems.
For instance, a solution for convex consensus trivially yields a solution for
vector consensus. More importantly, convex consensus can potentially be used to
solve other more interesting problems, such as convex function optimization [5,
4].

3
The categories of this paper are: physics
16
The categories of this paper are: stat
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph