309 citations · 454 across the 8 of their papers we have counts for
10 papers
Tensor Polynomial Additive Model
Yang Chen, Ce Zhu, Jiani Liu +1
Additive models can be used for interpretable machine learning for their clarity and simplicity. However, In the classical models for high-order data, the vectorization operation d…
TERM Model: Tensor Ring Mixture Model for Density Estimation
Ruituo Wu, Jiani Liu, Ce Zhu +3
Efficient probability density estimation is a core challenge in statistical machine learning. Tensor-based probabilistic graph methods address interpretability and stability concer…
Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs
Jiani Liu, Qinghua Tao, Ce Zhu +3
Multitask learning (MTL) leverages task-relatedness to enhance performance. With the emergence of multimodal data, tasks can now be referenced by multiple indices. In this paper, w…
Tensor Regression
Jiani Liu, Ce Zhu, Zhen Long +1
Regression analysis is a key area of interest in the field of data analysis and machine learning which is devoted to exploring the dependencies between variables, often using vecto…
Tensorized LSSVMs for Multitask Regression
Jiani Liu, Qinghua Tao, Ce Zhu +2
Multitask learning (MTL) can utilize the relatedness between multiple tasks for performance improvement. The advent of multimodal data allows tasks to be referenced by multiple ind…
Efficient Tensor Contraction via Fast Count Sketch
Xingyu Cao, Jiani Liu
Sketching uses randomized Hash functions for dimensionality reduction and acceleration. The existing sketching methods, such as count sketch (CS), tensor sketch (TS), and higher-or…
Hyperspectral Image Denoising with Partially Orthogonal Matrix Vector Tensor Factorization
Zhen Long, Yipeng Liu, Sixing Zeng +3
Hyperspectral image (HSI) has some advantages over natural image for various applications due to the extra spectral information. During the acquisition, it is often contaminated by…
Bayesian Low Rank Tensor Ring Model for Image Completion
Zhen Long, Ce Zhu, Jiani Liu +1
Low rank tensor ring model is powerful for image completion which recovers missing entries in data acquisition and transformation. The recently proposed tensor ring (TR) based comp…
AMP-Net: Denoising based Deep Unfolding for Compressive Image Sensing
Zhonghao Zhang, Yipeng Liu, Jiani Liu +2
Most compressive sensing (CS) reconstruction methods can be divided into two categories, i.e. model-based methods and classical deep network methods. By unfolding the iterative opt…
Provable Tensor Ring Completion
Huyan Huang, Yipeng Liu, Ce Zhu
Tensor completion recovers a multi-dimensional array from a limited number of measurements. Using the recently proposed tensor ring (TR) decomposition, in this paper we show that a…