Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: HYDRA: Competing convolutional kernels for fast and accurate time series
  classification   We demonstrate a simple connection between dictionary methods for time series
classification, which involve extracting and counting symbolic patterns in time
series, and methods based on transforming input time series using convolutional
kernels, namely ROCKET and its variants. We show that by adjusting a single
hyperparameter it is possible to move by degrees between models resembling
dictionary methods and models resembling ROCKET. We present HYDRA, a simple,
fast, and accurate dictionary method for time series classification using
competing convolutional kernels, combining key aspects of both ROCKET and
conventional dictionary methods. HYDRA is faster and more accurate than the
most accurate existing dictionary methods, and can be combined with ROCKET and
its variants to further improve the accuracy of these methods.

36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ex
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The categories of this paper are: acc-phys
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The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat