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Mathematics > Optimization and Control

Title: Complexity of Minimizing Regularized Convex Quadratic Functions

Abstract: In this work, we study the iteration complexity of gradient methods minimizing the class of uniformly convex regularized quadratic functions. We prove lower bounds on the functional residual of the form $\Omega(N^{-2p/(p-2)})$, where $p > 2$ is the power of the regularization term, and $N$ is the number of calls to a first-order oracle. A special case of our problem class is $p=3$, which is the minimization of cubically regularized convex quadratic functions. It naturally appears as a subproblem at each iteration of the cubic Newton method. The corresponding lower bound for $p = 3$ becomes $\Omega(N^{-6})$. Our result matches the best-known upper bounds on this problem class, rendering a sharp analysis of the minimization of uniformly convex regularized quadratic functions. We also establish new lower bounds on minimizing the gradient norm within our framework.
Subjects: Optimization and Control (math.OC)
Cite as: arXiv:2404.17543 [math.OC]
  (or arXiv:2404.17543v1 [math.OC] for this version)

Submission history

From: Daniel Berg Thomsen [view email]
[v1] Fri, 26 Apr 2024 17:13:55 GMT (39kb)

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