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Authors: Mariia Garkavenko, Hamid Mirisaee, Eric Gaussier, Agnès Guerraz, Cédric Lagnier 

First Online: 27 March 2021 

Abstract 

We address the problem of start-up valuation from a machine learning perspective with a focus on European start-ups. More precisely, we aim to infer the valuation of start-ups 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 start-up’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. 

Read the full text of the paper here  (not Open Access)

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