Reviews: Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
–Neural Information Processing Systems
The paper studies large-scale convex optimization algorithms based on the Newton method applied to regularized generalized self-concordant losses, in particular in ill-conditioned settings, providing new optimal generalization bounds and proofs of convergence. The reviewers found the contributions of high quality and were satisfied with the clarifications provided by the author response.
artificial intelligence, globally convergent newton method, ill-conditioned generalized self-concordant loss
Neural Information Processing Systems
Jan-24-2025, 04:13:22 GMT
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