The usual approach to developing and analyzing first-order methods for smooth convex optimization assumes that the gradient of the objective function is uniformly smooth with …
S Kousik, A Dai, GX Gao - IEEE Transactions on Automatic …, 2022 - ieeexplore.ieee.org
Ellipsoids are a common representation for reachability analysis, because they can be transformed efficiently under affine maps, and they allow conservative approximation of …
NT An, NM Nam, X Qin - Journal of Global Optimization, 2020 - Springer
The continuous k-center problem aims at finding k balls with the smallest radius to cover a finite number of given points in R^ n R n. In this paper, we propose and study the following …
EA Yildirim - SIAM Journal on Optimization, 2008 - SIAM
Given \calA:={a^1,\dots,a^m\}⊂R^n and ϵ>0, we propose and analyze two algorithms for the problem of computing a (1+ϵ)-approximation to the radius of the minimum enclosing ball …
We present a probabilistic registration algorithm that robustly solves the problem of rigid- body alignment between two shapes with high accuracy, by aptly modeling measurement …
S Park, J Park, CG Park - IEEE Transactions on Instrumentation …, 2020 - ieeexplore.ieee.org
In this article, the attitude estimation for low-cost MEMS inertial measurement units in a smartphone is proposed using adaptive ellipsoidal methods. Accelerometer and …
This paper contrasts recursive state space models and direct multi-step predictors for linear predictive control. We provide a tutorial exposition for both model structures to solve the …
R Zhao, RM Freund - Mathematical programming, 2023 - Springer
We present and analyze a new generalized Frank–Wolfe method for the composite optimization problem (P): min x∈ R nf (A x)+ h (x), where f is a θ-logarithmically …
A Rauh, L Jaulin - International Journal of Applied Mathematics …, 2021 - intapi.sciendo.com
A wide variety of approaches for set-valued simulation, parameter identification, state estimation as well as reachability, observability and stability analysis for nonlinear discrete …