Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robust and Accurate -- Compositional Architectures for Randomized
  Smoothing   Randomized Smoothing (RS) is considered the state-of-the-art approach to
obtain certifiably robust models for challenging tasks. However, current RS
approaches drastically decrease standard accuracy on unperturbed data, severely
limiting their real-world utility. To address this limitation, we propose a
compositional architecture, ACES, which certifiably decides on a per-sample
basis whether to use a smoothed model yielding predictions with guarantees or a
more accurate standard model without guarantees. This, in contrast to prior
approaches, enables both high standard accuracies and significant provable
robustness. On challenging tasks such as ImageNet, we obtain, e.g., $80.0\%$
natural accuracy and $28.2\%$ certifiable accuracy against $\ell_2$
perturbations with $r=1.0$. We release our code and models at
https://github.com/eth-sri/aces.

13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
30
The categories of this paper are: q-alg