Search Results for author: YaJing Li

Found 6 papers, 0 papers with code

Tensor Recovery Based on A Novel Non-convex Function Minimax Logarithmic Concave Penalty Function

no code implementations25 Jun 2022 HongBing Zhang, Xinyi Liu, Chang Liu, HongTao Fan, YaJing Li, Xinyun Zhu

The proposed function is generalized to tensor cases, yielding tensor MLCP and weighted tensor $L\gamma$-norm.

Low-Rank Tensor Completion Based on Bivariate Equivalent Minimax-Concave Penalty

no code implementations30 Jan 2022 HongBing Zhang, Xinyi Liu, HongTao Fan, YaJing Li, Yinlin Ye

To makes all the constant parameters of the MCP function as variables so that futherly improving the adaptability to the change of singular values in the LRTC problem, we propose the bivariate equivalent minimax-concave penalty (BEMCP) theorem.

Denoising

Tensor Full Feature Measure and Its Nonconvex Relaxation Applications to Tensor Recovery

no code implementations25 Sep 2021 HongBing Zhang, Xinyi Liu, HongTao Fan, YaJing Li, Yinlin Ye

Tensor sparse modeling as a promising approach, in the whole of science and engineering has been a huge success.

Two New Low Rank Tensor Completion Methods Based on Sum Nuclear Norm

no code implementations6 Aug 2021 HongBing Zhang, Xinyi Liu, HongTao Fan, YaJing Li, Yinlin Ye

This paper proposes a new tensor $L_{2, 1}$ norm minimization model (TLNM) that integrates sum nuclear norm (SNN) method, differing from the classical tensor nuclear norm (TNN)-based tensor completion method, with $L_{2, 1}$ norm and Qatar Riyal decomposition for solving the LRTC problem.

A statistical fat-tail test of predicting regulatory regions in the Drosophila genome

no code implementations21 Feb 2014 Jian-Jun Shu, YaJing Li

A statistical study of cis-regulatory modules (CRMs) is presented based on the estimation of similar-word set distribution.

Hypercomplex cross-correlation of DNA sequences

no code implementations21 Feb 2014 Jian-Jun Shu, YaJing Li

Using hypercomplex number representation, conventional sequence analysis method, such as, dot matrix analysis, dynamic programming, and cross-correlation method are extended and improved to align the DNA sequences with fuzzy composition.

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