Sparse Matricized Tensor Times Khatri-Rao Prod-uct (spMTTKRP) is the most time-
consuming compute kernel in sparse tensor decomposition. In this paper, we introduce a …

Sparse compiler is a promising solution for sparse tensor algebra optimization. In compiler
implementation, reduction in sparse-dense hybrid algebra plays a key role in performance …

High-dimensional sparse data emerge in many critical application domains such as
cybersecurity, healthcare, anomaly detection, and trend analysis. To quickly extract …

Sparse matrix computation is crucial in various modern applications, including large-scale
graph analytics, deep learning, and recommender systems. The performance of sparse …

Tensor factorization plays a fundamental role in multiple areas of AI research. Nevertheless,
it encounters significant challenges related to privacy breaches and operational efficiency. In …

Tensor completion is a prevailing method for predicting the unobserved or missing data in
incomplete tensors. In many real-world scenarios, incomplete tensors can grow in multiple …