A research team led by Professor Jaesik Choi of KAIST's Kim Jaechul Graduate School of AI, in collaboration with KakaoBank Corp, has developed an accelerated explanation technology that can explain ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Sharat Potharaju is cofounder and CEO of Uniqode, whose vision is to enable digital connection with every physical object and place. Third-party cookies are crumbling, customer acquisition costs are ...

Artur is a copywriter and SEO specialist, as well as a small business owner. In his free time, he loves to play computer games and is glad that he was able to connect his professional career with his ...

One of the main uses of QR decomposition A=QR is in solving the linear least squares problem Ax=b. In order to solve this problem, the only access we need of Q is the ability to apply it (or its ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

Posts from this topic will be added to your daily email digest and your homepage feed. You don’t need an app for this —your phone can do it already. You don’t need an app for this —your phone can do ...

Shoppers staring at product labels frequently ask themselves, "Is this product actually sustainable?" While 68% of respondents from my company's 2024 consumer survey said that sustainability is ...

As you gather all the last-minute holiday packages arriving at your doorstep, be careful about any that you didn't order or ones that don't have a return address and want you to scan a QR code: it ...

Abstract: We consider computing the QR factorization with column pivoting (QRCP) for a tall and skinny matrix, which has important applications including low-rank approximation and rank determination.