Results 161 to 170 of about 3,678,430 (211)

Non-Local Robust Quaternion Matrix Completion for Large-Scale Color Image and Video Inpainting

IEEE Transactions on Image Processing, 2022
The image nonlocal self-similarity (NSS) prior refers to the fact that a local patch often has many nonlocal similar patches to it across the image and has been widely applied in many recently proposed machining learning algorithms for image processing ...
Zhigang Jia, Qiyu Jin, M. Ng, Xile Zhao
semanticscholar   +1 more source

Feature and Nuclear Norm Minimization for Matrix Completion

IEEE Transactions on Knowledge and Data Engineering, 2022
Matrix completion, whose goal is to recover a matrix from a few entries observed, is a fundamental model behind many applications. Our study shows that, in many applications, the to-be-complete matrix can be represented as the sum of a low-rank matrix ...
Mengyun Yang, Yaohang Li, Jianxin Wang
semanticscholar   +1 more source

Network Completion: Beyond Matrix Completion

2021 International Conference on Information Networking (ICOIN), 2021
Due to practical reasons such as limited resources and privacy settings specified by users on social media, most network data tend to be only partially observed with both missing nodes and missing edges. Thus, it is of paramount importance to infer the missing parts of the networks since incomplete network data may severely degrade the performance of ...
Cong Tran, Won-Yong Shin
openaire   +1 more source

A Novel Enriched Version of Truncated Nuclear Norm Regularization for Matrix Completion of Inexact Observed Data

IEEE Transactions on Knowledge and Data Engineering, 2022
In recent years, matrix completion has become one of the main concepts in data science. Truncated nuclear norm regularization (TNNR) approximation of the rank function is an example of the favorite approaches in matrix completion that performs better ...
Tayyebeh Saeedi, M. Rezghi
semanticscholar   +1 more source

Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction

Bioinform., 2020
MOTIVATION Predicting the association between microRNAs (miRNAs) and diseases plays an import role in identifying human disease-related miRNAs. As identification of miRNA-disease associations via biological experiments is time-consuming and expensive ...
Jin Li, Sai Zhang, Tao Liu, Chen Ning, Zhuoxuan Zhang, Wei Zhou   +5 more
semanticscholar   +1 more source

Unsigned Matrix Completion

2021 IEEE International Symposium on Information Theory (ISIT), 2021
Inspired by real phase retrieval and low-rank matrix recovery, we introduce the problem of unsigned matrix retrieval, where the aim is to recover a matrix of bounded-rank from a sign-ambiguous version of it. Allowing for missing entries in addition to sign ambiguities leads to the problem of unsigned matrix completion.
Yunzhen Yao, Liangzu Peng, Manolis C. Tsakiris   +2 more
openaire   +1 more source

IMCHGAN: Inductive Matrix Completion With Heterogeneous Graph Attention Networks for Drug-Target Interactions Prediction

IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2021
Identification of targets among known drugs plays an important role in drug repurposing and discovery. Computational approaches for prediction of drug–target interactions (DTIs)are highly desired in comparison to traditional biological experiments as its
Jin Li, Jingru Wang, Hao Lv, Zhuoxuan Zhang, Zaixia Wang   +4 more
semanticscholar   +1 more source

Matrix completion by deep matrix factorization

Neural Networks, 2018
Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations.
Jicong Fan, Jieyu Cheng
openaire   +2 more sources

Sound source localization of non-synchronous measurements beamforming with block Hermitian matrix completion

, 2021
In this work, the block Hermitian matrix completion (BHMC) method, a fast non-iteration algorithm to complete the cross-spectral matrix, is proposed to realize the sound source localization of the non-synchronous measurements beamforming.
Fangli Ning, Jiahao Song, Jinglong Hu, Juan Wei   +3 more
semanticscholar   +1 more source

Coupling Matrix Reconfiguration Based on Matrix Completion

IEEE transactions on microwave theory and techniques
This article proposes a general and efficient filter topology reconfiguration method based on matrix completion theory, which allows for frequency-dependent couplings (FDCs) and nonresonating nodes (NRNs). The projected gradient of the objective function
Yi Zeng, Huijin Huang, Yang Wu, Yafei Sun, Ying Xiang Xu, Ming Yu   +5 more
semanticscholar   +1 more source