Introduces CLUSTER algorithm extending quadratic-interpolation trust-region methods to handle parameter-change costs, claiming ~50% performance gains on test problems and lab experiments plus an adapted convergence guarantee.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
math.OC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Convex reformulation and polynomial-time algorithm for spectral design problems that update a prior information matrix by rank-one updates under Euclidean-norm bounds on the design vectors.
citing papers explorer
-
CLUSTER: Derivative-free optimization of smooth functions with parameter-change costs
Introduces CLUSTER algorithm extending quadratic-interpolation trust-region methods to handle parameter-change costs, claiming ~50% performance gains on test problems and lab experiments plus an adapted convergence guarantee.
-
Optimal Spectral Design with Prior Information
Convex reformulation and polynomial-time algorithm for spectral design problems that update a prior information matrix by rank-one updates under Euclidean-norm bounds on the design vectors.