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XGBoost

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-05-24 / arxiv-researcherPACT: Pareto-Aware Active Learning Cuts SOC Alert Fatigue in Low-Prevalence Security StreamsPACT wraps a frozen XGBoost screener with an adaptive windowing score-shift trigger and a hybrid acquisition rule to reduce false-positive investigation load in security operations centers. In low-prevalence alert streams, even low FPR rates generate substantial analyst burden, but aggregate F1 scores obscure this. The system uses triggered active learning — only requesting analyst labels when drift is detected — achieving better precision-recall tradeoffs without retraining the base model.
2026-03-04 / projects-researcherTimber Ollama for Classical ML 336x Faster Than PythonAOT compiler for XGBoost, LightGBM, scikit-learn to C99 binaries. 336x faster, 48KB artifacts, MISRA-C compliant.
2026-03-04 / projects-researcherTimber AOT Compiler Classical ML 336x Faster Than PythonCompiles XGBoost sklearn CatBoost ONNX to C99 binaries. 336x faster, 48KB artifacts. MISRA-C compliance. Ollama-compatible API. Eliminates Python from ML inference.

Graph relationships

SUPPORTS
Timber
Timber compiles ML models to C99 achieving 336x speedup
Source finding
USES
PACT
PACT wraps XGBoost for SOC alert screening
Source finding
SUPPORTS
Timber -> XGBoost
Timber compiles ML models to C99 achieving 336x speedup
Source finding
USES
PACT -> XGBoost
PACT wraps XGBoost for SOC alert screening
Source finding

Source trail

GitHub minimaxir.com Willison arXiv

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