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A little bit of context. Basically, all of tabular deep learning has been stuck and SOTA has been tree based algorithms like Catboost and XGBoost. This seems l
by snats 3y ago
A little bit of context.
Basically, all of tabular deep learning has been stuck and SOTA has been tree based algorithms like Catboost and XGBoost. This seems like a big step forward towards getting a generalizable deep learning model besides this "tree models"
- mistrial9 3y agoCatboost and XGBoost do not need to be replaced
- spyder 3y agoYea, and from this paper it looks like the tree model (Catboost supervised) is still beating their (zero-shot) performance and they don't show their supervised version yet, but they write at the end that they plan to do it in a future work. Will be interesting to see.
- ipsum2 3y agoThis isn't for tabular data though? Time series transformers have been around for a few years now, see Transformers in Time Series: A Survey https://arxiv.org/abs/2202.07125 https://arxiv.org/abs/2202.07125 and Are Transformers Effective for Time Series Forecasting? https://arxiv.org/abs/2205.13504 https://arxiv.org/abs/2205.13504