Frank Hutter
A leading scholar in the AutoML field and machine learning researcher, whose work focuses on automated machine learning, neural architecture search, and hyperparameter optimization.
Timeline (last 90 days)
Frank Hutter is co-CEO of PriorLabs and a former professor of machine learning.
Frank Hutter believes tabular data is very dirty, which is one of the reasons it took deep learning a long time to truly handle it well.
Frank Hutter noted that TabNet was once heavily hyped and received thousands of citations, but failed to generalize to new datasets.
Frank Hutter believes tabular data requires a large number of tables from diverse domains, because knowledge cannot be transferred across tables at the level of individual rows.
Frank Hutter believes that transfer in tabular data should occur at the pattern level rather than the row level, and that in-context learning is the key technique for achieving this transfer.
Prior Labs是一家源自德国弗莱堡大学AutoML实验室的研究团队，该实验室由Frank Hutter教授领导
弗莱堡大学 AutoML 实验室由 Frank Hutter 教授领导，曾推出 Auto-sklearn、BOHB、SMAC 等 AutoML 工具
All Facts (7)
Frank Hutter is co-CEO of PriorLabs and a former professor of machine learning.
50%UnverifiedFrank Hutter believes tabular data is very dirty, which is one of the reasons it took deep learning a long time to truly handle it well.
50%UnverifiedFrank Hutter noted that TabNet was once heavily hyped and received thousands of citations, but failed to generalize to new datasets.
50%UnverifiedFrank Hutter believes tabular data requires a large number of tables from diverse domains, because knowledge cannot be transferred across tables at the level of individual rows.
50%UnverifiedFrank Hutter believes that transfer in tabular data should occur at the pattern level rather than the row level, and that in-context learning is the key technique for achieving this transfer.
50%UnverifiedPrior Labs是一家源自德国弗莱堡大学AutoML实验室的研究团队，该实验室由Frank Hutter教授领导
50%Unverified弗莱堡大学 AutoML 实验室由 Frank Hutter 教授领导，曾推出 Auto-sklearn、BOHB、SMAC 等 AutoML 工具
50%