Diagnose schemas, analyze EXPLAIN plans, rank slow queries, recommend indexes, design partitions, run benchmarks, and self-learn from research papers — all from a single CLI.
Abstract: DataFrame libraries are widely adopted in data science for their flexible, Pythonic interfaces, but their fragmented APIs and unstructured query patterns limit systematic optimization.
Mechanism-level reproduction of Google's Nested Learning (HOPE) architecture (HOPE blocks, CMS, and Self‑Modifying TITANs), matching the quality bar set by lucidrains' TITAN reference while remaining ...
Abstract: Bilevel optimization, where one optimization problem is inherently nested within another, has gained significant attention due to its extensive applications in machine learning, such as ...
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