What unifies algebra is the practice of studying things—like the moves you can make on a Rubik's cube or the numbers on a clock face you use to tell time—and the way they behave when you put ...

Then later on, maybe at night, if I’ve done everything I need to, I’ve done all my P-sets, I’m studied up, I’ve done all I need to do for football, I can relax.

The proof technique combines prior knowledge of PDE theory and randomized numerical linear algebra techniques and may lead to practical benefits such as improving dataset and neural network ...

Seminar Title: Scaling Constrained Low-rank Approximations. Name: School of CSE Ph.D. Student Koby Hayashi Date: Wednesday, April 17, 2024 at 12:00 pm Location: Coda Building, 13th Floor, Conference ...

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly ...

We present and analyze three randomized algorithms to approximate von Neumann entropy of real density matrices: our algorithms leverage recent developments in the Randomized Numerical Linear Algebra ...

They are curious to learn precisely how little data is necessary to train these algorithms while producing accurate results. The researchers used randomized numerical linear algebra and PDE theory to ...

We present a simple method based on randomized numerical linear algebra for efficiently computing approximate top eigendecompositions, which can be used to replace large matrices (such as Hessians and ...