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Data leakage

topic2 events
papersTODAY 04:00 UTC

arXiv Paper Proposes Leakage-Safe ML for Grid Job Runtime Prediction

A new arXiv preprint examines how machine learning models for predicting job runtimes in grid and distributed computing should be validated without data leakage. The authors argue that evaluation must reflect real deployment constraints, since overly optimistic results can mislead scheduling-aware resource management. The work revisits CPU burst time prediction with these safeguards in mind.

arxiv/machine-learning/scheduling/research
papersTODAY 04:00 UTC

Site-Disjoint Study Finds No Consistent NIR Advantage for Agricultural Traversability

A new arXiv paper compares near-infrared and standard color imaging for daytime farm-machinery traversability using a site-disjoint evaluation that removes spatial data leakage. The authors find NIR does not consistently beat color once frames from the same locations are kept out of both training and test splits, and note that earlier benchmarks reporting an NIR edge used sequence-level splits. The work suggests sensor choices for agricultural perception should be revisited on properly separated data.

computer-vision/agriculture/benchmarks/robotics