AIBullisharXiv – CS AI · Apr 106/10
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In-Context Decision Making for Optimizing Complex AutoML Pipelines
Researchers propose PS-PFN, an advanced AutoML method that extends traditional algorithm selection and hyperparameter optimization to handle modern ML pipelines with fine-tuning and ensembling. Using posterior sampling and prior-data fitted networks for in-context learning, the approach outperforms existing bandit and AutoML strategies on benchmark tasks.