Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayes DistNet -- A Robust Neural Network for Algorithm Runtime
  Distribution Predictions   Randomized algorithms are used in many state-of-the-art solvers for
constraint satisfaction problems (CSP) and Boolean satisfiability (SAT)
problems. For many of these problems, there is no single solver which will
dominate others. Having access to the underlying runtime distributions (RTD) of
these solvers can allow for better use of algorithm selection, algorithm
portfolios, and restart strategies. Previous state-of-the-art methods directly
try to predict a fixed parametric distribution that the input instance follows.
In this paper, we extend RTD prediction models into the Bayesian setting for
the first time. This new model achieves robust predictive performance in the
low observation setting, as well as handling censored observations. This
technique also allows for richer representations which cannot be achieved by
the classical models which restrict their output representations. Our model
outperforms the previous state-of-the-art model in settings in which data is
scarce, and can make use of censored data such as lower bound time estimates,
where that type of data would otherwise be discarded. It can also quantify its
uncertainty in its predictions, allowing for algorithm portfolio models to make
better informed decisions about which algorithm to run on a particular
instance.

12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
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The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: funct-an
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The categories of this paper are: bayes-an