Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Abstract: Distributed computations, such as distributed matrix multiplication, can be vulnerable to significant security issues, notably Byzantine attacks. These attacks may target either worker nodes ...

This paper came across my feed that implements sparse matrix-vector multiplication. Sparse matrix-vector multiplication (SpMV) is a fundamental operation in scientific computing, data analysis, and ...

Researchers at DeepSeek on Monday released a new experimental model called V3.2-exp, designed to have dramatically lower inference costs when used in long-context operations. DeepSeek announced the ...

Performing dense*sparse matrix multiplication using a CuSparseMatrixCOO does not yield the correct result. In the example below, dense*sparse spmm is performed correctly when using a CuSparseMatrixCSC ...

You can now order an “Iron Dome” for mosquitoes. Its name is the Photon Matrix, a black box about the size of a smartphone that can detect, track, and eliminate mosquitoes mid-flight using an ...

Samuel is Collider's List Flex Editor (previously Lead List Editor), which means he's pretty much always hovering around Collider's List department. A writing and editing automaton based in Nashville, ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...