A quantile-regression ensemble with safety factor reduces under-allocated jobs from 4.17% to 2.89% and average overallocation from 148% to 44.51% on SAP build data.
Tabular data: Deep learning is not all you need
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Entity embeddings reach AUC-ROC 0.9612 on IEEE-CIS fraud data, statistically tied with CatBoost and superior to tier group encoding (0.9548), with CatBoost leading on AUC-PR.
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Optimizing Memory Allocation in Distributed Clusters with Predictive Modeling
A quantile-regression ensemble with safety factor reduces under-allocated jobs from 4.17% to 2.89% and average overallocation from 148% to 44.51% on SAP build data.
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Interpretable vs Learned Encoders for High-Cardinality Fraud Detection
Entity embeddings reach AUC-ROC 0.9612 on IEEE-CIS fraud data, statistically tied with CatBoost and superior to tier group encoding (0.9548), with CatBoost leading on AUC-PR.