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pro vyhledávání: '"Azorin, Raphael"'
Tabular data is ubiquitous in many real-life systems. In particular, time-dependent tabular data, where rows are chronologically related, is typically used for recording historical events, e.g., financial transactions, healthcare records, or stock hi
Externí odkaz:
http://arxiv.org/abs/2406.15327
While the promises of Multi-Task Learning (MTL) are attractive, characterizing the conditions of its success is still an open problem in Deep Learning. Some tasks may benefit from being learned together while others may be detrimental to one another.
Externí odkaz:
http://arxiv.org/abs/2301.02873