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Valuation of Startups: A Machine Learning Perspective

Hamid Mirisaee
  • Function : Author
Éric Gaussier
Agnès Guerraz
  • Function : Author
Cédric Lagnier
  • Function : Author


We address the problem of startup valuation from a machine learning perspective with a focus on European startups. More precisely, we aim to infer the valuation of startups corresponding to the funding rounds for which only the raised amount was announced. To this end, we mine Crunchbase, a well-established source of information on companies. We study the discrepancy between the properties of the funding rounds with and without the startup’s valuation announcement and show that the Domain Adaptation framework is suitable for this task. Finally, we propose a method that outperforms, by a large margin, the approaches proposed previously in the literature.
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hal-03368116 , version 1 (06-10-2021)



Mariia Garkavenko, Hamid Mirisaee, Éric Gaussier, Agnès Guerraz, Cédric Lagnier. Valuation of Startups: A Machine Learning Perspective. Advances in Information Retrieval, 12656, Springer International Publishing, pp.176-189, 2021, Lecture Notes in Computer Science, ⟨10.1007/978-3-030-72113-8_12⟩. ⟨hal-03368116⟩
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