Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient ...

Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.

Discover how QXO, Inc. drives growth in building-products distribution with digital transformation and smart acquisitions.

My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

Background: Plant-based diets with reduced animal protein intake are increasingly recommended for health and sustainability reasons that have potential implications for nutrient intake, including ...

In an era dominated by social media, misinformation has become an all too familiar foe, infiltrating our feeds and sowing seeds of doubt and confusion. With more than half of social media users across ...

Abstract: This article proposes the row-stochastic event-based quantized (RSEQ) algorithm to address the distributed optimization problem with multiple communication constraints, including limited ...

The old Babylonian algorithm, a remarkable mathematical artifact from ancient Mesopotamia (around 1800–1600 BC), has long been a subject of fascination to scholars. This ancient algorithm not only ...

You might have heard that algorithms are in control of everything you hear, read, and see. They control the next song on your Spotify playlist, or what YouTube suggests you watch after you finish a ...

Social media platforms are more than just tools for sharing cat videos or keeping up with friends—they're powerful influencers of public opinion. The algorithms that drive these platforms determine ...