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The finite-difference time-domain (FDTD) algorithm is a popular numerical method for solving electromagnetic problems. FDTD simulations can suffer from instability due to the explicit nature of the method. Stability enforcement can be…

Computational Engineering, Finance, and Science · Computer Science 2018-12-26 Fadime Bekmambetova , Xinyue Zhang , Piero Triverio

Finite mixture modelling is a popular method in the field of clustering and is beneficial largely due to its soft cluster membership probabilities. A common method for fitting finite mixture models is to employ spectral clustering, which…

Machine Learning · Statistics 2024-03-22 Liam Welsh , Phillip Shreeves

Delay embedding---a method for reconstructing dynamical systems by delay coordinates---is widely used to forecast nonlinear time series as a model-free approach. When multivariate time series are observed, several existing frameworks can be…

Machine Learning · Statistics 2019-07-04 Shunya Okuno , Kazuyuki Aihara , Yoshito Hirata

We study the problem of evaluating the excess risk of large-scale empirical risk minimization under the square loss. Leveraging the idea of wild refitting and resampling, we assume only black-box access to the training algorithm and develop…

Machine Learning · Computer Science 2026-04-03 Haichen Hu , David Simchi-Levi

Climate change necessitates rapid expansion of renewable energy, with wind energy offering a scalable and low-impact solution. However, accurate prediction of wind loads and power generation remains challenging due to uncertainties in wind…

Fluid Dynamics · Physics 2026-04-30 Omar Sallam , Mirjam Fürth

This paper proposes a computational framework for the design optimization of stable structures under large deformations by incorporating nonlinear buckling constraints. A novel strategy for suppressing spurious buckling modes related to…

Computational Engineering, Finance, and Science · Computer Science 2023-06-07 Guodong Zhang , Kapil Khandelwal , Tong Guo

Top-down induction of decision trees has been observed to suffer from the inadequate functioning of the pruning phase. In particular, it is known that the size of the resulting tree grows linearly with the sample size, even though the…

Artificial Intelligence · Computer Science 2011-06-06 T. Elomaa , M. Kaariainen

Efficient optimization of topology and raster angle has shown unprecedented enhancements in the mechanical properties of 3D printed materials. Topology optimization helps reduce the waste of raw material in the fabrication of 3D printed…

Graphics · Computer Science 2022-06-08 Ahmed Moter , Mohamed Abdelhamid , Aleksander Czekanski

This paper studies two fundamental problems in power systems: the economic dispatch problem (EDP) and load shedding. For the EDP, an extension of the problem considering the transmission losses is presented. Because the optimization problem…

Systems and Control · Electrical Eng. & Systems 2021-08-31 Ismi Rosyiana Fitri , Jung-Su Kim

Integrated with a high share of Inverter-Based Resources (IBRs), microgrids face increasing complexity of frequency dynamics, especially after unintentional islanding from the maingrid. These IBRs, on the other hand, provide more control…

Systems and Control · Electrical Eng. & Systems 2024-02-22 Zhongda Chu , Guoxuan Cui , Fei Teng

Stochastic gradient algorithms are often unstable when applied to functions that do not have Lipschitz-continuous and/or bounded gradients. Gradient clipping is a simple and effective technique to stabilize the training process for problems…

Optimization and Control · Mathematics 2021-06-11 Vien V. Mai , Mikael Johansson

The paper addresses an optimal control problem for a perturbed sweeping process of the rate-independent hysteresis type described by a controlled "play and stop" operator with separately controlled perturbations. This problem can be reduced…

Optimization and Control · Mathematics 2015-12-01 Tan H. Cao , Boris S. Mordukhovich

The $\alpha$-modeling strategy is followed to derive a new subgrid parameterization of the turbulent stress tensor in large-eddy simulation (LES). The LES-$\alpha$ modeling yields an explicitly filtered subgrid parameterization which…

Chaotic Dynamics · Physics 2007-05-23 Bernard J. Geurts , Darryl D. Holm

The dual formulation for linear elasticity, in contrast to the primal formulation, is not affected by locking, as it is based on the stresses as main unknowns. Thus it is quite attractive for nearly incompressible and incompressible…

Numerical Analysis · Mathematics 2021-06-28 Gabriele Rovi , Rolf Krause

This study focusses on self-balancing microgrids to smartly utilize and prevent overdrawing of available power capacity of the grid. A distributed framework for automated distribution of optimal power demand is proposed, where all building…

Systems and Control · Computer Science 2017-01-20 Meenakshi Chatterjee

A scale-resolving simulation methodology that includes stochastic energy backscatter is incorporated into a proprietary block-structured compressible flow solver. Particular attention is devoted to the discretisation of the convective terms…

Fluid Dynamics · Physics 2025-11-12 Angelo Passariello , Pietro Catalano , Carmine De Lucia , Renato Tognaccini

The entropy regularization is inspired by information entropy from machine learning and the ideas of exploration and exploitation in reinforcement learning, which appears in the control problem to design an approximating algorithm for the…

Optimization and Control · Mathematics 2024-11-21 Ziyue Chen , Qi Zhang

In Navier-Stokes turbulence, a bottleneck effect in the energy cascade near the viscous cutoff causes an overshoot in the energy spectrum, or spectral bump, relative to Kolmogorov's -5/3 scaling. A similar overshoot occurs in large-eddy…

Fluid Dynamics · Physics 2025-09-24 Mostafa Kamal , Perry L. Johnson

There is increasing demand for automated systems that can fabricate 3D structures. Robotic spatial extrusion has become an attractive alternative to traditional layer-based 3D printing due to a manipulator's flexibility to print large,…

Robotics · Computer Science 2020-02-07 Caelan Reed Garrett , Yijiang Huang , Tomás Lozano-Pérez , Caitlin Tobin Mueller

We develop a probabilistic method for assessing the tail behavior and geometric stability of one-dimensional n i.i.d. samples by tracking how their span contracts when the most extreme points are trimmed. Central to our approach is the…

Machine Learning · Statistics 2025-09-03 Erwan Dereure , Emmanuel Akame Mfoumou , David Holcman
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