AI RESEARCH
IGT-OMD: Implicit Gradient Transport for Decision-Focused Learning under Delayed Feedback
arXiv CS.LG
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ArXi:2605.12693v1 Announce Type: new Decision-focused learning trains predictive models end-to-end against downstream decision loss, but online settings suffer delayed feedback: outcomes may not arrive for many environment interactions. We identify \emph{staleness amplification}, a failure mode unique to bilevel optimization under delay, in which gradient staleness couples with inner-solver sensitivity to inflate regret beyond single-level delay theory.