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 challenging tasks in numerical ...
Engines Podcast The Engines of Our Ingenuity 2514: Linear Algebra and Netflix Episode: 2514 How Netflix uses linear algebra to determine what movies you will like best. Today, UH math professor Krešo ...
Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Matrix multiplications (MatMul) are the ...
Abstract: A system-on-chip (SoC) photonic-electronic linear-algebra accelerator with the features of wavelength-division-multiplexing (WDM) based broadband photodetections and high-dimensional ...
It’s the year 2199, and things look incredibly bleak for humanity. After an AI uprising, the surviving humans are stockpiled in pods and harvested as an energy source, powering a race of machines. The ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback