Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: T-CGAN: Conditional Generative Adversarial Network for Data Augmentation
  in Noisy Time Series with Irregular Sampling   In this paper we propose a data augmentation method for time series with
irregular sampling, Time-Conditional Generative Adversarial Network (T-CGAN).
Our approach is based on Conditional Generative Adversarial Networks (CGAN),
where the generative step is implemented by a deconvolutional NN and the
discriminative step by a convolutional NN. Both the generator and the
discriminator are conditioned on the sampling timestamps, to learn the hidden
relationship between data and timestamps, and consequently to generate new time
series. We evaluate our model with synthetic and real-world datasets. For the
synthetic data, we compare the performance of a classifier trained with
T-CGAN-generated data, against the performance of the same classifier trained
on the original data. Results show that classifiers trained on T-CGAN-generated
data perform the same as classifiers trained on real data, even with very short
time series and small training sets. For the real world datasets, we compare
our method with other techniques of data augmentation for time series, such as
time slicing and time warping, over a classification problem with unbalanced
datasets. Results show that our method always outperforms the other approaches,
both in case of regularly sampled and irregularly sampled time series. We
achieve particularly good performance in case with a small training set and
short, noisy, irregularly-sampled time series.

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The categories of this paper are: hep-th
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
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The categories of this paper are: econ
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The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: nlin
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The categories of this paper are: hep-lat
2
The categories of this paper are: math
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The categories of this paper are: acc-phys