Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

Subjects: “…stochastic gradient descent; variance reduction; convex optimization; non-convex optimization; convergence rate…”
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Stochastic Variance Reduced Primal–Dual Hybrid Gradient Methods for Saddle-Point Problems by Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu

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Pricing basket options using Monte Carlo simulation employing Cholesky decomposition and variance reduction techniques under the 2D stochastic Black–Scholes equation by Youness Saoudi, Khalid Jeaab, Hanaa Hachimi

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The effect of sampling methods on the validity and reliability of the estimation of the orbital stability of human gait by Jeongin Moon, Jooeun Ahn

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Joint production and sustainability investment decisions for a risk-averse manufacturer under a Cap-and-trade policy by Hongling Lu, Qingguo Bai, Fanwen Meng

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Polynomial estimates of measurand parameters for data from bimodal mixtures of exponential distributions by S.V. Zabolotnii, V.Yu. Kucheruk, Z.L. Warsza, А.K. Khassenov

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Parameter Estimation of a Partially Observed Hypoelliptic Stochastic Linear System by Nilton O. B. Ávido, Paula Milheiro-Oliveira

“…The simulation results indicate that, as the variance of the observation error vanishes, the proposed approach remains reasonably close to the output of the EM algorithm, with the advantage of a significant reduction in computing time.…”
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The Neural Correlates and Behavioral Impact of Peripheral Noise Electrical Stimulation on Motor Learning by Li-Wei Chou, Man-Wai Kou, Hui-Min Lee, Felipe Fregni, Vincent Chen, Chung-Lan Kao

“…Noise electrical stimulation significantly reduced the force error both during and post motor learning (p <0.05) and required less time to reach a plateau of force error (p <0.05); however, for percipients who received sham stimulation first, the effect of noise on learning may not be optimal and thus not represent the net effect of stochastic resonance. For neural activities in the brain, noise electrical stimulation induced an immediate reduction in the EEG beta (15-30 Hz) band and gamma (>30 Hz) CMC. …”
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Optimal control via FBSDE with dynamic risk penalization: a structuring formulation based on Pontryagin's principle by Kayembe Tcheick, Mubenga Kamputo Pascal, Bofeki Bosonga, Eugene Mbuyi Mukendi

“…Numerical simulations across multiple scenarios validate the robustness of the proposed method, demonstrating a significant reduction in terminal wealth variance compared to classical approaches. …”
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Research on the application of improved MCMC algorithm in the measurement of high-dimensional financial data by Naijia Liu, Yuchao Su

“…A parallelized Markov chain Monte Carlo algorithm based on wavelet transform is developed to effectively reduce the difficulty of multivariate stochastic fluctuation modeling and Bayesian inference by decomposing the original data with high frequency and filtering noise reduction based on the wavelet theory; secondly, an adaptive process and a multi-chain parallel sampling method are introduced to adjust the sample generating mechanism of the multivariate stochastic fluctuation model. …”
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Geocaulosphere soil bacterial community drives potato common scab outcomes beyond pathogen abundance by Wenchong Shi, Minghao Lv, Ruiqi Wang, Muhammad Saleem, Lujun Wang, Mingcong Li, Bing Wang, Rongshan Lin, Bingjie Xu, Chunyu Yang, Tangyuan Ning, Bo Zhou, Zheng Gao

“…Across four Shandong fields, PCS-infected GS exhibited an 11.66% reduction in bacterial α-diversity (Shannon index) and elevated stochastic community assembly. …”
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Breakdown of the compositional data approach in psychometric Likert scale big data analysis: about the loss of statistical power of two-sample t-tests applied to heavy-tailed big d... by René Lehmann, Bodo Vogt

“…This increase in statistical power is observed when the central limit theorem (CLT) holds true in statistics. Through stochastic simulation, this study explores the impact of violating the CLT on statistical power of the unpaired t-test under heavy-tailed data generating processes (DGPs) with finite variance. …”
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Demand side management with electric vehicles and optimal renewable resources integration under system uncertainties by Mohamed Mostafa Eissa, Rania Abdel Wahed Swief, Tarek Saad Abdel Salam

“…Taking into consideration the stochastic behavior of RERs, EVs demand elasticity of charging and discharging scenarios and load variance. …”
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Metagenomic insights into surface sediment microbial community and functional composition along a water-depth gradient in a subtropic deep lake by Peixuan Zhang, Peixuan Zhang, Minglei Ren, Yan Xu, Jianjun Wang

“…Although water depth was the most important driver in explaining 29.9 and 26.5% of variance in microbial and functional gene composition, stochastic processes primarily governed the community assemblages, particularly dispersal limitation with the contribution of 43.7%. …”
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A Combination of Classification Robust Adaptive Kalman Filter with PPP-RTK to Improve Fault Detection for Integrity Monitoring of Autonomous Vehicles by Hassan Elsayed, Ahmed El-Mowafy, Amir Allahvirdi-Zadeh, Kan Wang, Xiaolong Mi

“…Epoch-wise weighting adjustments in the robustness test create a more accurate stochastic model, aided by an adaptive unit weight variance (UWV) calculated with a sliding window, achieving a 7–28% UWV reduction. …”
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A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…The method leverages a Stochastic Variational Gaussian Process with a Linear Model of Coregionalization, incorporating physical models like manufacturer power curves as mean functions and enabling flexible modeling of active power and its associated variance. …”
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Rate-induced transitions and noise-driven resilience in vegetation pattern dynamics by L. Vanderveken, M. Crucifix

“…Perturbations modelled as Gaussian stochastic processes with specific autocorrelation structures were applied to the system. …”
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Analytic Solutions for the Stationary Seismic Response of Three-Dimensional Structures with a Tuned Mass-Inerter Damper and Bracket by Lin Deng, Cong Yao, Xinguang Ge

“…Secondly, analytical expressions for spectral moments and variances of seismic responses are obtained. Finally, four numerical examples are presented to investigate the following: (1) verification of the proposed response solutions, showing that the calculation time of the proposed method is approximately 1/500 of that of the traditional method; (2) examination of spatial effects in 3D structures under unidirectional excitation, revealing that structural seismic responses in the direction along the earthquake ground motion is approximately 10⁴ times that in the direction perpendicular to the ground motion; (3) investigation of the spatial dynamic characteristics of a 3D structure subjected to unidirectional seismic excitation, showing that the bracket parameters significantly affect the damping effects on an EDS; and (4) application of the optimization method for the damper’s parameters that considers system dynamic reliability and different weights of the damper’s parameters as constraints, indicating that the most economical damping parameters can achieve a reduction in displacement spectral moments by 30–50%. …”
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SSR_VibraProfiler: a Python package for accurate classification of varieties using SSRs with intra-variety specificity and inter-variety polymorphism by Chenhao Jiang, Chuan Dong, Zhenzhen Wu, Chenyi Shi, Qiannan Ye, Xiaopei Wu, Siyi Ma, Yuming Wen, Guoping Yu, Jiasheng Wu, Chengjun Zhang

“…We use t-SNE (t-distributed Stochastic Neighbor Embedding) to project the matrix onto a two-dimensional plane, followed by K-means clustering of the individuals. …”
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Fundamental properties and characteristics of flux distribution tallies using proper orthogonal decomposition by Kondo Ryoichi, Yamamoto Akio, Endo Tomohiro

“…The POD tallies can achieve dimensionality and statistical uncertainty reduction for a finely discretized flux distribution. …”
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