New analysis without global strong convexity yields tight scaling laws: NS error ~Θ(kd/n²) and NS-IF difference ~Θ((k+d)√(kd)/n²) for well-behaved logistic regressions.
Newflu- ence: Boosting model interpretability and understanding in high dimensions.arXiv preprint arXiv:2507.11895,
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On the Accuracy of Newton Step and Influence Function Data Attributions
New analysis without global strong convexity yields tight scaling laws: NS error ~Θ(kd/n²) and NS-IF difference ~Θ((k+d)√(kd)/n²) for well-behaved logistic regressions.