33 citations · 36 across the 5 of their papers we have counts for
3 papers · 1 filter
Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation
Jan Laukemann, Ahmed E. Helal, S. Isaac Geronimo Anderson +7
High-dimensional sparse data emerge in many critical application domains such as healthcare and cybersecurity. To extract meaningful insights from massive volumes of these multi-di…
Efficient, Out-of-Memory Sparse MTTKRP on Massively Parallel Architectures
Andy Nguyen, Ahmed E. Helal, Fabio Checconi +6
Tensor decomposition (TD) is an important method for extracting latent information from high-dimensional (multi-modal) sparse data. This study presents a novel framework for accele…
ALTO: Adaptive Linearized Storage of Sparse Tensors
Ahmed E. Helal, Jan Laukemann, Fabio Checconi +4
The analysis of high-dimensional sparse data is becoming increasingly popular in many important domains. However, real-world sparse tensors are challenging to process due to their…