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Aleksander Obuchowski

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2 papers
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2

AAAI Conference 2024 Short Paper

Target-Free Domain Adaptation through Cross-Adaptation (Student Abstract)

  • Aleksander Obuchowski
  • Barbara Klaudel
  • Piotr Frąckowski
  • Sebastian Krajna
  • Wasyl Badyra
  • Michał Czubenko
  • Zdzisław Kowalczuk

The population characteristics of the datasets related to the same task may vary significantly and merging them may harm performance. In this paper, we propose a novel method of domain adaptation called "cross-adaptation". It allows for implicit adaptation to the target domain without the need for any labeled examples across this domain. We test our approach on 9 datasets for SARS-CoV-2 detection from complete blood count from different hospitals around the world. Results show that our solution is universal with respect to various classification algorithms and allows for up to a 10pp increase in F1 score on average.

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AAAI Conference 2020 Short Paper

Transformer-Capsule Model for Intent Detection (Student Abstract)

  • Aleksander Obuchowski
  • Michał Lew

Intent recognition is one of the most crucial tasks in NLU systems, which are nowadays especially important for designing intelligent conversation. We propose a novel approach to intent recognition which involves combining transformer architecture with capsule networks. Our results show that such architecture performs better than original capsule-NLU network implementations and achieves state-of-the-art results on datasets such as ATIS, AskUbuntu, and WebApp.

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