Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PAC-Bayes bounds for stable algorithms with instance-dependent priors   PAC-Bayes bounds have been proposed to get risk estimates based on a training
sample. In this paper the PAC-Bayes approach is combined with stability of the
hypothesis learned by a Hilbert space valued algorithm. The PAC-Bayes setting
is used with a Gaussian prior centered at the expected output. Thus a novelty
of our paper is using priors defined in terms of the data-generating
distribution. Our main result estimates the risk of the randomized algorithm in
terms of the hypothesis stability coefficients. We also provide a new bound for
the SVM classifier, which is compared to other known bounds experimentally.
Ours appears to be the first stability-based bound that evaluates to
non-trivial values.

27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph