12 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.DC2022
cuFasterTucker: A Stochastic Optimization Strategy for Parallel Sparse FastTucker Decomposition on GPU Platform
Zixuan Li
Currently, the size of scientific data is growing at an unprecedented rate. Data in the form of tensors exhibit high-order, high-dimensional, and highly sparse features. Although t…
cs.DC2022
cu_FastTucker: A Faster and Stabler Stochastic Optimization for Parallel Sparse Tucker Decomposition on Multi-GPUs
Zixuan Li
High-Order, High-Dimension, and Sparse Tensor (HOHDST) data originates from real industrial applications, i.e., social networks, recommender systems, bio-information, and traffic i…
cs.DC2020★ 12 cited
SGD_Tucker: A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition
Hao Li, Zixuan Li, Kenli Li +3
Sparse Tucker Decomposition (STD) algorithms learn a core tensor and a group of factor matrices to obtain an optimal low-rank representation feature for the \underline{H}igh-\under…