Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in
  Machine Learning   Optimizing nonconvex (NCVX) problems, especially nonsmooth and constrained
ones, is an essential part of machine learning. However, it can be hard to
reliably solve such problems without optimization expertise. Existing
general-purpose NCVX optimization packages are powerful but typically cannot
handle nonsmoothness. GRANSO is among the first optimization solvers targeting
general nonsmooth NCVX problems with nonsmooth constraints, but, as it is
implemented in MATLAB and requires the user to provide analytical gradients,
GRANSO is often not a convenient choice in machine learning (especially deep
learning) applications. To greatly lower the technical barrier, we introduce a
new software package called NCVX, whose initial release contains the solver
PyGRANSO, a PyTorch-enabled port of GRANSO incorporating auto-differentiation,
GPU acceleration, tensor input, and support for new QP solvers. NCVX is built
on freely available and widely used open-source frameworks, and as a highlight,
can solve general constrained deep learning problems, the first of its kind.
NCVX is available at https://ncvx.org, with detailed documentation and numerous
examples from machine learning and other fields.

21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
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The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-th
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The categories of this paper are: acc-phys