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Chen Cheng, Ruiting Liang, Rina Foygel Barber
· 1 min read
ResearcharXiv cs.LG
Rolling Conformal Prediction in Sequential Model Training
arXiv:2609.26951v1 Announce Type: cross
Abstract: We introduce Rolling Conformal Prediction (rolling-CP), a distribution-free predictive inference method for the setting of sequential model training. Specifically, given a data stream $(X_1,Y_1),(X_2,Y_2),\dots$, at each time $n$ the trained model may depend on the observed history $\{(X_i,Y_i)\}_{i
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This story was published by arXiv cs.LG and written by Chen Cheng, Ruiting Liang, Rina Foygel Barber. SyncAI.news shows a preview; the complete article is on the publisher's site.
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