Yunsoo Ha

College of Engineering

Works (2)

Updated: December 9th, 2024 08:35

2024 article

Iteration complexity and finite-time efficiency of adaptive sampling trust-region methods for stochastic derivative-free optimization

Ha, Y., & Shashaani, S. (2024, April 3). IISE TRANSACTIONS, Vol. 4.

By: Y. Ha n & S. Shashaani n 

author keywords: Simulation optimization; zeroth-order oracle; finite-time performance
TL;DR: It is proved that the adaptive sampling with interpolation-based trust regions or ASTRO-DF has a canonical iteration complexity of $\mathcal{O}(\epsilon^{-2})$ almost surely, which is the first guarantee of its kind without placing assumptions on the quality of function estimates or model quality or independence between them. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: April 1, 2024

2023 journal article

Latency considerations for stochastic optimizers in variational quantum algorithms

QUANTUM, 7.

By: M. Menickelly*, Y. Ha n & M. Otten *

TL;DR: Stochastic optimization algorithms that yield stochastic processes emulating the dynamics of classical deterministic algorithms results in methods with theoretically superior worst-case iteration complexities, at the expense of greater per-iteration sample (shot) complexities. (via Semantic Scholar)
Source: Web Of Science
Added: June 5, 2023

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