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In the field of gestural action recognition, many studies have focused on dimensionality reduction along the spatial axis, to reduce both the variability of gestural sequences expressed in the reduced space, and the computational complexity…

Machine Learning · Computer Science 2014-09-18 Pierre-François Marteau , Sylvie Gibet , Clement Reverdy

In the light of regularized dynamic time warping kernels, this paper re-considers the concept of time elastic centroid for a setof time series. We derive a new algorithm based on a probabilistic interpretation of kernel alignment matrices.…

Machine Learning · Computer Science 2019-07-12 Pierre-François Marteau

We present a finite element discretisation to model the interaction between a poroelastic structure and an elastic medium. The consolidation problem considers fully coupled deformations across an interface, ensuring continuity of…

Numerical Analysis · Mathematics 2023-06-21 S. Badia , M. Hornkjøl , A. Khan , K. -A. Mardal , A. F. Martín , R. Ruiz-Baier

The parallel alternating direction method of multipliers (ADMM) algorithms have gained popularity in statistics and machine learning due to their efficient handling of large sample data problems. However, the parallel structure of these…

Statistics Theory · Mathematics 2024-04-11 Xiaofei Wu , Jiancheng Jiang , Zhimin Zhang

Efficient modeling of dispersive materials via time-domain simulations of the Maxwell equations relies on the technique of auxiliary differential equations. In this approach, a material's frequency-dependent permittivity is represented via…

We apply the framework of tempered fractional calculus to investigate the spatial dispersion of elastic waves in a one-dimensional elastic bar characterized by range-dependent nonlocal interactions. The measure of the interaction is given…

Materials Science · Physics 2016-04-28 Vikash Pandey , Sven Peter Näsholm , Sverre Holm

We consider a continuous-space and continuous-time diffusion process under resetting with memory. A particle resets to a position chosen from its trajectory in the past according to a memory kernel. Depending on the form of the memory…

Statistical Mechanics · Physics 2017-11-29 Denis Boyer , Martin R. Evans , Satya N. Majumdar

We consider the prediction problem of a continuous-time stochastic process on an entire time-interval in terms of its recent past. The approach we adopt is based on functional kernel nonparametric regression estimation techniques where…

Statistics Theory · Mathematics 2007-06-13 Anestis Antoniadis , Efstathios Paparoditis , Theofanis Sapatinas

A time domain system of equations is proposed to model elastic wave propagation in an unbounded two-dimensional anisotropic solid using perfectly matched layer (PML). Starting from a system of first-order frequency domain stress-velocity…

Computational Physics · Physics 2013-12-16 Hisham Assi , Richard S. C. Cobbold

Non-uniform time stepping in acoustic propagation models can be used to preserve accuracy or reduce computational cost for an acoustic simulation with a wave front propagating through a domain with both heterogeneous and homogenous regions,…

Numerical Analysis · Mathematics 2025-07-11 Matthew J. King , B. E. Treeby , B. T. Cox

This paper concerns the Time-Domain Full Waveform Inversion (FWI) for dispersive and dissipative poroelastic materials. The forward problem is an initial boundary value problem (IBVP) of the poroelastic equations with a memory term; the FWI…

Numerical Analysis · Mathematics 2022-01-24 Miao-jung Yvonne Ou , Petr Plecháč , Jiangming Xie

We introduce an approach to determining the required waveforms to coherently control the optical energy localization in plasmonic nanosystems. This approach is based on the impulsive localized excitation of the nanosystem and time reversal…

Disordered Systems and Neural Networks · Physics 2007-05-23 Xiangting Li , Mark I. Stockman

We consider scattered data approximation on product regions of equal and different dimensionality. On each of these regions, we assume quasi-uniform but unstructured data sites and construct optimal sparse grids for scattered data…

Numerical Analysis · Mathematics 2026-04-24 Michael Griebel , Helmut Harbrecht , Michael Multerer

It is well-known that the high computational complexity and the insufficient samples in large-scale array signal processing restrict the real-world applications of the conventional full-dimensional adaptive beamforming (sample matrix…

Information Theory · Computer Science 2014-05-20 Hu Xie , Da-Zheng Feng , Ming-Dong Yuan

Understanding the time evolution of physical systems is crucial to revealing fundamental characteristics that are hidden in frequency domain. In optical science, high-quality resonance cavities and enhanced interactions with matters are at…

Optics · Physics 2021-09-22 Yingheng Tang , Jichao Fan , Xinwei Li , Jianzhu Ma , Minghao Qi , Cunxi Yu , Weilu Gao

Selecting an appropriate kernel is a central challenge in kernel-based spectral methods. In \emph{Kernelized Diffusion Maps} (KDM), the kernel determines the accuracy of the RKHS estimator of a diffusion-type operator and hence the quality…

Machine Learning · Statistics 2026-04-21 Othmane Aboussaad , Adam Miraoui , Boumediene Hamzi , Houman Owhadi

In the era of big data, it is desired to develop efficient machine learning algorithms to tackle massive data challenges such as storage bottleneck, algorithmic scalability, and interpretability. In this paper, we develop a novel efficient…

Machine Learning · Computer Science 2022-11-14 Jinshan Zeng , Minrun Wu , Shao-Bo Lin , Ding-Xuan Zhou

In this paper, a temporal nonuniform $L1$ type difference scheme is built up for the time fractional diffusion-wave equation with the help of the order reduction technique. The unconditional convergence of the nonuniform difference scheme…

Numerical Analysis · Mathematics 2023-03-01 Hong Sun , Yanping Chen , Xuan Zhao

This paper discusses the local linear smoothing to estimate the unknown first and second infinitesimal moments in second-order jump-diffusion model based on Gamma asymmetric kernels. Under the mild conditions, we obtain the weak consistency…

Statistics Theory · Mathematics 2017-07-07 Yuping Song , Hanchao Wang

Statistical learning methods show great promise in providing an accurate prediction of materials and molecular properties, while minimizing the need for computationally demanding electronic structure calculations. The accuracy and…

Materials Science · Physics 2018-01-24 Andrea Grisafi , David M. Wilkins , Gábor Csányi , Michele Ceriotti