no code implementations • 7 Jan 2019 • Longhao Yuan, Chao Li, Jianting Cao, Qibin Zhao
Dimensionality reduction is an essential technique for multi-way large-scale data, i. e., tensor.
no code implementations • 7 Sep 2018 • Longhao Yuan, Chao Li, Danilo Mandic, Jianting Cao, Qibin Zhao
In this paper, by exploiting the low-rank structure of the TR latent space, we propose a novel tensor completion method which is robust to model selection.
no code implementations • 22 May 2018 • Longhao Yuan, Chao Li, Danilo Mandic, Jianting Cao, Qibin Zhao
In low-rank tensor completion tasks, due to the underlying multiple large-scale singular value decomposition (SVD) operations and rank selection problem of the traditional methods, they suffer from high computational cost and high sensitivity of model complexity.
1 code implementation • 5 Apr 2018 • Longhao Yuan, Qibin Zhao, Lihua Gui, Jianting Cao
We propose two TT-based algorithms: Tensor Train Weighted Optimization (TT-WOPT) and Tensor Train Stochastic Gradient Descent (TT-SGD) to optimize TT decomposition factors.
no code implementations • 7 Nov 2017 • Longhao Yuan, Qibin Zhao, Jianting Cao
In this paper, we aim at the problem of tensor data completion.
1 code implementation • 8 Sep 2017 • Longhao Yuan, Qibin Zhao, Jianting Cao
In this paper, we aim at the completion problem of high order tensor data with missing entries.