Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Abstract: Training machine learning models often involves solving high-dimensional stochastic optimization problems, where stochastic gradient-based algorithms are hindered by slow convergence.
IBM researchers unveil quantum algorithm achieving potential exponential speedup for solving chaotic differential equations, with implications for fusion energy and climate modeling. IBM researchers ...
Dynamical low-rank approximation (DLRA) is an emerging tool for reducing computational costs and provide memory savings when solving high-dimensional problems. In this work, we propose and analyze a ...
Abstract: We consider a nonlinear discrete stochastic control system, and our goal is to design afeedback control policy in order to lead the system to a prespecified state. We adopt a Stochastic ...
PSEB releases model papers for classes 8-12 to help students prepare. The 2026 English exam includes 25% objective-type questions. The exam is 3 hours, with 80 marks for theory and 20 for assessment.
SDEvelo represents a significant advancement in the analysis of single-cell RNA sequencing (scRNA-seq) data, offering a novel approach to inferring RNA velocity through multivariate stochastic ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results