Overview of <i>Mottle</i>’s sequence distance estimation algorithm. by Alisa Prusokiene (18196228)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)

Accuracy of Fed-GLMM and meta-analysis estimates relative to the gold-standard pooled analysis. by Zhiyu Yan (74647)

Absolute relative bias of Fed-GLMM and meta-analysis estimates relative to gold-standard pooled analysis across simulation replicates. by Zhiyu Yan (74647)

Comparison of computation time and estimate accuracy for Fed-GLMM and meta-analysis relative to gold-standard pooled analysis with increasing computing nodes/EHR subsets. by Zhiyu Yan (74647)

Estimated coefficients from the Best Linear Projection (BLP) of on . by Vishalie Shah (7301909)

Estimated coefficients from the Best Linear Projection (BLP) of on . by Vishalie Shah (7301909)

Supplementary Material for: Automated Detection and Diameter Estimation for Mouse Mesenteric Artery Using Semantic Segmentation by Higaki A. (11035161)

“…However, this procedure requires technical expertise for sample preparation and effort to choose an appropriate sized artery. In this study, we developed an automatic artery/vein differentiation and a size measurement system utilizing machine learning algorithms. …”

Modeling Pregnancy Outcomes Through Sequentially Nested Regression Models by Xuan Bi (3096897)

“…Our approach explicitly bridges the connections across nested outcomes through computationally easy algorithms and enjoys theoretical guarantee of estimation and variable selection. …”

Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model by Getachew S. Molla (6416744)

“…The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …”

Distributed Estimation of Principal Support Vector Machines for Sufficient Dimension Reduction by Jun Jin (551362)

“…To address this issue, we propose a naive and a refined distributed estimation algorithms for fast implementation when the sample size is large. …”

Distributed Decoding From Heterogeneous 1-Bit Compressive Measurements by Canyi Chen (13532043)

“…<p>We develop a communication-efficient distributed estimation for the 1-bit compressive sensing where unknown sparse signals are coded into binary measurements with noises and sign flips. …”

Pre-processing of raw images for pose estimation using physical model-trained convolutional neural network model. by Aniket Ravan (3174171)

NuSeT efficiently addresses common segmentation challenges. by Linfeng Yang (516708)

Table 1 - by Daniela Sele (9749590)

Table_1_Identification of sources of DIF using covariates in patient-reported outcome measures: a simulation study comparing two approaches based on Rasch family models.DOCX by Yseulys Dubuy (16809567)

“…The performance of the algorithms was assessed using: (i) the rates of false and correct detection of DIF, (ii) the DIF size and form recovery, and (iii) the bias in the latent variable level estimation. …”

Comparison of penalized logistic regression models for rare event case by Hülya Olmuş (7494017)

“…With this aim, LR, Firth LR, FLIC and FLAC methods were compared in terms of parameter estimation bias, predicted probability bias and Root Mean Squared Error (RMSE) for different sample sizes, event and correlation rates conducting a detailed Monte Carlo simulation study. …”

Adaptive Inference for Change Points in High-Dimensional Data by Yangfan Zhang (6451946)

“…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …”