Training today’s largest neural networks is limited by backpropagation’s sequential updates and Graphics Processing Unit (GPU) bound compute and energy, slowing scaling. We demonstrate a hybrid ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Nowadays, frontiers among different sciences are revealed as diffuse, and as a ...
In the past few decades, multi-linear algebra also known as tensor algebra has been adapted and employed as a tool for various engineering applications. Recent developments in tensor algebra have ...
Abstract: Random data sketching (or projection) is now a classical technique enabling, for instance, approximate numerical linear algebra and machine learning algorithms with reduced computational ...
Most of today’s quantum algorithms may not achieve practical speedups. Material science and chemistry have a huge potential and we hope more practical algorithms will be invented based on our ...
Abstract: In recent years, a variety of randomized constructions of sketching matrices have been devised, that have been used in fast algorithms for numerical linear algebra problems, such as least ...
Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
Edited by Joel E. Cohen, The Rockefeller University, New York, NY, and approved December 6, 2011 (received for review August 23, 2011) These results were found for finite-dimensional models. But the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results