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Practical Skills Demand Forecasting via Representation Learning of Temporal Dynamics. (arXiv:2205.09508v1 [econ.GN])
May 20, 2022, 1:12 a.m. | Maysa M. Garcia de Macedo, Wyatt Clarke, Eli Lucherini, Tyler Baldwin, Dilermando Queiroz Neto, Rogerio de Paula, Subhro Das
cs.LG updates on arXiv.org arxiv.org
Rapid technological innovation threatens to leave much of the global
workforce behind. Today's economy juxtaposes white-hot demand for skilled labor
against stagnant employment prospects for workers unprepared to participate in
a digital economy. It is a moment of peril and opportunity for every country,
with outcomes measured in long-term capital allocation and the life
satisfaction of billions of workers. To meet the moment, governments and
markets must find ways to quicken the rate at which the supply of skills reacts …
arxiv dynamics forecasting learning representation representation learning skills temporal
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