HLRTF: Hierarchical low-rank tensor factorization for inverse problems in multi-dimensional imaging
Inverse problems in multi-dimensional imaging, eg, completion, denoising, and compressive
sensing, are challenging owing to the big volume of the data and the inherent ill-posedness …
sensing, are challenging owing to the big volume of the data and the inherent ill-posedness …
Exploring hardware fault impacts on different real number representations of the structural resilience of tcus in gpus
The most recent generations of graphics processing units (GPUs) boost the execution of
convolutional operations required by machine learning applications by resorting to …
convolutional operations required by machine learning applications by resorting to …
Tensor completion through total variation with initialization from weighted hosvd
In our paper, we have studied the tensor completion problem when the sampling pattern is
deterministic. We first propose a simple but efficient weighted HOSVD algorithm for recovery …
deterministic. We first propose a simple but efficient weighted HOSVD algorithm for recovery …