Distributed block coordinate descent for minimizing partially separable functions

J Mareček, P Richtárik, M Takáč - … : NAO-III, Muscat, Oman, January 2014, 2015‏ - Springer
A distributed randomized block coordinate descent method for minimizing a convex function
of a huge number of variables is proposed. The complexity of the method is analyzed under …

Deep learning enhanced internet of medical things to analyze brain computed tomography images of stroke patients

B Omarov, A Tursynova, M Uzak - International Journal of …, 2023‏ - search.proquest.com
In the realm of advancing medical technology, this paper explores a revolutionary
amalgamation of deep learning algorithms and the Internet of Medical Things (IoMT) …

[PDF][PDF] Digital stethoscope for early detection of heart disease on phonocardiography data

B Omarov, A Tuimebayev, R Abdrakhmanov… - International Journal of …, 2023‏ - academia.edu
The burgeoning realm of digital healthcare has unveiled a novel diagnostic instrument: a
digital stethoscope tailored for the early detection of heart disease as elucidated in this …

[PDF][PDF] Applying Artificial Intelligence and Computer Vision for Augmented Reality Game Development in Sports

N Omarov, B Omarov, A Baibaktina… - International …, 2023‏ - pdfs.semanticscholar.org
This paper delineates the intricate process of crafting an Augmented Reality (AR)-enriched
version of the Subway Surfers game, engineered with an emphasis on action recognition …

Cooling mechanisms in 3D ICs: Thermo-mechanical perspective

SG Kandlikar, D Kudithipudi… - 2011 International …, 2011‏ - ieeexplore.ieee.org
Three-dimensional (3D) integrated circuits (IC) impose several challenges in thermal
management. Stacking vertical layers significantly increases the heat dissipation per unit …

Parallel SMO algorithm implementation based on OpenMP

P Chang, Z Bi, Y Feng - 2014 IEEE International Conference on …, 2014‏ - ieeexplore.ieee.org
Sequential minimal optimization (SMO) algorithm is widely used for solving the optimization
problem during the training process of support vector machine (SVM). However, the SMO …

A scalable algorithm for multi-class support vector machine on geo-distributed datasets

T Kabir, MA Adnan - … International Conference on Big Data (Big …, 2019‏ - ieeexplore.ieee.org
Training machine learning models on large scale data to efficiently discover valuable
information while maintaining the security and privacy of data remains an important research …

Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem

MAHB Sulaiman, A Suliman… - Proceedings of the 6th …, 2014‏ - ieeexplore.ieee.org
This paper presents performance evaluation of GPU-accelerated Support Vector Machines
(SVMs) using large datasets. Although SVMs algorithm is popular among machine learning …

Predict Turnaround Time of Hospital Discharge

B Jia, J Zhang, X Jia - 2022 IEEE/WIC/ACM International Joint …, 2022‏ - ieeexplore.ieee.org
COVID-19 pandemics lead to further shortages of beds globally. Ningbo No. 1 Hospital
implemented an integrated digital management system to tackle inefficiency in the discharge …

Performance Comparison of Parallel Execution Using GPU and CPU in SVM Training Session

NSM Salleh, MF Baharim - 2015 4th International Conference …, 2015‏ - ieeexplore.ieee.org
Support Vector Machine (SVM) is a machine learning approach, which is used in a growing
number of applications. SVM is a useful technique for data classification. This machine …