ICML "linear models" Papers

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Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data

Yvonne Zhou, Mingyu Liang, Ivan Brugere et al.

ICML 2024poster

Local vs. Global Interpretability: A Computational Complexity Perspective

Shahaf Bassan, Guy Amir, Guy Katz

ICML 2024spotlight