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One-shot learning has become an important research topic in the last decade with many real-world applications. The goal of one-shot learning is to classify unlabeled instances when there is only one labeled example per class. Conventional problem set
Externí odkaz:
http://arxiv.org/abs/2201.09202
Distance metric learning has attracted much attention in recent years, where the goal is to learn a distance metric based on user feedback. Conventional approaches to metric learning mainly focus on learning the Mahalanobis distance metric on data at
Externí odkaz:
http://arxiv.org/abs/2011.04062
Mining tasks over sequential data, such as clickstreams and gene sequences, require a careful design of embeddings usable by learning algorithms. Recent research in feature learning has been extended to sequential data, where each instance consists o
Externí odkaz:
http://arxiv.org/abs/1911.00949
Publikováno v:
In Pattern Recognition February 2018 74:406-421
Publikováno v:
Machine Learning, June 2018, Special Issue of the ECML PKDD 2018 Journal Track, ISSN: 0885-6125
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1093::7139b0bbf8723b058b206ceea47636f5
http://www.eurecom.fr/publication/5589
http://www.eurecom.fr/publication/5589
Publikováno v:
Pattern Recognition, Volume 74, February 2018
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1093::5f0e824643796cbf184e7aa250da407b
http://www.eurecom.fr/publication/5334
http://www.eurecom.fr/publication/5334
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