6 papers · 1 filter
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…
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…
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…