Spark Policy Toolkit supplies semantic contracts plus mapInPandas/mapInArrow inference and executor-side split search so policy learning remains correct and fast on Spark clusters up to tens of millions of rows.
MMLSpark: Unifying machine learning ecosystems at massive scales
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
An urgency-aware adaptation of the Deep Interest Network with temporal encodings and listwise neuralNDCG loss delivers a 9% nDCG@1 lift over an optimized LightGBM baseline on a 650k-user industrial DFS dataset.
citing papers explorer
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Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark
Spark Policy Toolkit supplies semantic contracts plus mapInPandas/mapInArrow inference and executor-side split search so policy learning remains correct and fast on Spark clusters up to tens of millions of rows.
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Driving Engagement in Daily Fantasy Sports with a Scalable and Urgency-Aware Ranking Engine
An urgency-aware adaptation of the Deep Interest Network with temporal encodings and listwise neuralNDCG loss delivers a 9% nDCG@1 lift over an optimized LightGBM baseline on a 650k-user industrial DFS dataset.