arxiv
PublishedMay 29, 2026 at 4:00 AM
Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction
Publisher summary· verbatim
arXiv:2605.25297v2 Announce Type: replace-cross Abstract: Effective features are crucial for predictive model performance, but creating them often requires domain expertise, limiting scalability across applications. We define feature engineering as an agentic code generation problem: features are no
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning18harxivOptical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning18harxivDynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models18harxivTemporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents18hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗