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cs.LG2026
The price of multi-group transductive learning
Noah Bergam, Samuel Deng, Daniel Hsu
We show every multi-group learner in the leave-one-out transductive setting may incur a surprisingly large multiplicative penalty in its error rate on some group relative to the er…
cs.LG2026
Fixed Universal Transformers
Jingwen Liu, Alexandr Andoni, Daniel Hsu
We introduce \emph{universal transformers}: fixed transformers that can simulate any transformer in a given class via a suitable input embedding. Analogous to a universal Turing ma…