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math.OC2026
Optimal Parameter-Free Second-order Acceleration with Inexact Hessians under Generalized Smoothness
Artem Agafonov, Aslan Ashabokov, Alexander D'yakonov +3
We study second-order convex optimization under generalized Hessian smoothness, where the local Hessian Lipschitz constant may grow linearly with the gradient norm. For inexact Hes…
math.OC2026
Decentralized Inexact Cubic Newton Method with Consensus Procedure
Artem Agafonov, Anton Novitskii, Alexander Rogozin +5
Distributed optimization is widely used in large-scale and privacy-preserving machine learning, where each agent stores a local objective and communicates only with its neighbors i…