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Learning Source Structure: Bayesian Prediction with Transformers

Feder, Meir et al.
arXiv (All) · Papers
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machine-learning
A transformer trained on sequences whose source parameters are drawn afresh each time can learn only what the sequences share: the source family and its prior. The Bayesian predictor that knows both, which we call informed Bayes, is the unique minimizer of the training loss and is computable from th
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