12 papers · ranked by Valyu relevance
Radu Ioan Boţ, Dang-Khoa Nguyen, Chunxiang Zong
In this paper, we derive a Fast Reflected Forward-Backward (Fast RFB) algorithm to solve the problem of finding a zero of the sum of a maximally monotone operator and a monotone and Lipschitz continuous operator in a real Hilbert space. Our approach extends the class of reflected forward-backward methods by introducing…
Jing Wu, Wenbo Li, Lijun Su, Huiru Wang + 2 more
In this paper, we present a modified nonmonotone line search algorithm that employs a variable parameter to control the degree of nonmonotonicity. This modification enhances both the probability of identifying the global minimum and the rate of convergence. Within the framework of alternating nonnegative least squares…
Theodoros Anagnostopoulos, Evanthia Zervoudi, Christos Anagnostopoulos, Apostolos Christopoulos + 1 more
Linear regression analysis focuses on predicting a numeric regressand value based on certain regressor values. In this context, k-Nearest Neighbors (k-NN) is a common non-parametric regression algorithm, which achieves efficient performance when compared with other algorithms in literature. In this research effort an…
Yan Xia, Dandan Li, Songhua Wang, Mohamed Kamel Riahi
In this paper, a hybrid conjugate gradient projection method for finding solutions of constrained nonlinear equations is proposed by integrating both hyperplane projection and hybrid techniques. The key features of this method are as follows: (1) It is characterized by a low storage requirement and relies solely on…
Oleg Stepanov, Alexey Isaev, Elena Dranitsyna, Yulia Litvinenko
A class of nonlinear filtering problems connected with data fusion from various navigation sensors and a navigation system is considered. A special feature of these problems is that the posterior probability density function (PDF) of the state vector being estimated changes its character from multi-extremal to…
Shijun Hao, Xi Pan, Yanbin Liang, Kaiwei Wu + 3 more
The precise ranging of ultra-wideband (UWB) fuzes relies on extracting time delay information from echo signals. However, ground multipath propagation effects induce a significant time-delay spread in the echo signals. This manifests as a channel impulse response (CIR) composed of numerous, closely spaced components…
Anas Abdelkarim, Daniel Görges, Holger Voos
Factor graph optimization serves as a fundamental framework for robotic perception, enabling applications such as pose estimation, simultaneous localization and mapping (SLAM), structure-from-motion (SfM), and situational modeling. Traditionally, these methods solve unconstrained least squares problems using algorithms…
Amir Hossein Salehi Shayegan
Time-fractional diffusion equations have emerged as powerful models for describing anomalous transport phenomena in physics, biology and engineering. To address the computational challenges arising from their non-local operators, we employ the WEB-spline finite element method, which provides a flexible and accurate…
Hao Dong, Yuedong Wang
The neighborhood selection method directly explores the conditional dependence structure and has been widely used to construct undirected graphical models. However, except for some special cases with discrete data, there is little research on nonparametric methods for neighborhood selection with mixed data. This paper…
Xuan Lin
This paper presents a comparative study of data-driven acceleration techniques for mixed-integer bilinear programs (MIBLPs) applied to robot motion planning. MIBLPs combine discrete decision variables and nonlinear constraints, making them computationally challenging for real-time robotics applications. We investigate…
Yury Zabegaev, Inga Berre, Eirik Keilegavlen
Modeling multiphysics processes in porous media requires preconditioned iterative linear solvers to enable efficient simulations at industry-relevant scales. These solvers are typically composed of sub-algorithms that target individual physical processes. Various options are available for each algorithm, with the…
Amir Hossein Salehi Shayegan
In this work, we present a solution to the critical limitation of qubit capacity in near-term quantum hardware by giving a hybrid framework that integrates the spectral element method (SEM) with distributed quantum computing. Using domain decomposition techniques, the additive and multiplicative Schwarz methods, the…