This project implements a CVaR-minimizing portfolio optimization model based on the seminal paper "Optimization of Conditional Value-at-Risk" by Rockafellar and Uryasev (2000). The analysis uses ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

Already registered? Click here to login now. Linear electromagnetic devices — such as linear motors, generators, actuators, and magnetic gears — play a vital role in precision motion control, energy ...

To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. CSE Core Courses are classified into six areas: Introduction to CSE, Computational Mathematics, High Performance ...

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad \textrm{s.t.}~ \quad L \leq Ax \leq ...

The growing demand for energy-efficient Wireless Sensor Networks (WSNs) in applications such as IoT, environmental monitoring, and smart cities has sparked exhaustive research into practical solutions ...

The objective of the 3D-SCALO problem is to assign the given components to optimal mounting surfaces and position them at the best locations, while satisfying the requirements for (1) heat dissipation ...

This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary data ...