In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...

If it feels like social platforms suddenly “get” you more than they used to, you’re not imagining it! In 2026, feeds aren’t only reacting to what you click anymore. They’re predicting what you ...

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 ...

ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...

Hand-tuned WebAssembly implementations for efficient execution of web-based sparse computations including Sparse Matrix-Vector Multiplication (SpMV), sparse triangular solve (SpTS) and other useful ...

SpMV-CNN: A set of convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product ...

Abstract: We consider a sparse matrix-matrix multiplication (SpGEMM) setting where one matrix is square and the other is tall and skinny. This special variant, TS-SpGEMM, has important applications in ...

The increasing energy demands of AI pose a significant challenge to sustainability and decarbonization goals. Researchers have discovered a new integer-addition algorithm that could reduce AI's energy ...

ABSTRACT: In this paper we compare track data association purity, accuracy, and timing on a simple, idealized model tracking problem for two data association methods: Global Nearest Neighbor (GNN) and ...