Abstract: This article proposes an expectation maximization sample transfer identification (EM-STI) algorithm to address the parameter identification problem in dynamic systems with nonideal data.

new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript “Our brains are being melted by the algorithm.” [MUSIC PLAYING] “Attention is infrastructure.” “Those algorithms are ...

Mr. Conte is the co-founder and chief executive of Patreon. The World Wide Web was introduced some three decades ago. Describing in 2019 the hopes that had been projected onto the internet at its ...

There are mornings when I wake up feeling a heaviness that resembles grief, a dread that the America I have loved and known is slipping away. It's not just the daily onslaught of cruelty and falsehood ...

Forbes contributors publish independent expert analyses and insights. Anisha Sircar is a journalist covering tech, finance and society. A preliminary TikTok deal proposes U.S. investors own 80% of its ...

Diccon Hyatt is an experienced financial and economics reporter. He's written hundreds of articles breaking down complex financial topics in plain language, emphasizing the impact that economic ...

Mr. Pankaj Vasani, Group CFO at Cube Highways InvIT, has been in leadership roles at Publicis Groupe, Vodafone, Coca-Cola and Subros. As I stood facing a roomful of analysts, each poring over our ...

Ever wondered how social media platforms decide how to fill our feeds? They use algorithms, of course, but how do these algorithms work? A series of corporate leaks over the past few years provides a ...

Jake Peterson is Lifehacker’s Tech Editor, and has been covering tech news and how-tos for nearly a decade. His team covers all things technology, including AI, smartphones, computers, game consoles, ...

Imagine this: you’re in the middle of an important project, juggling deadlines, and collaborating with a team scattered across time zones. Suddenly, your computer crashes, and hours of work vanish in ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...