2026 7th International Conference on Computer Engineering and Application (ICCEA 2026)

Chair: Prof. Xin Luo, Dean of College of Computer and Information Science · School of Software, Southwest University (IEEE/AAIA Fellow)

Introduction:

With the rapid growth of multimodal, heterogeneous, and high-dimensional data, tensors have become an important mathematical tool for modeling complex structured data. Traditional tensor learning methods usually assume regular structures or standard tensor formats. However, in many real-world applications, data often exhibit non-standard tensor characteristics, such as high-order sparse tensors, incomplete tensors, heterogeneous coupled tensors, dynamic tensors, and tensors with complex structural constraints. These types of data widely arise in applications including intelligent transportation, recommender systems, computer vision, bioinformatics, and scientific computing, posing new challenges for representation learning.

This special session aims to bring together recent advances in representation learning for non-standard tensor data, focusing on novel theories, models, and applications. In particular, the session will explore how to develop efficient and robust learning methods for complex tensor structures under scenarios such as missing data, dynamic evolution, and multimodal coupling. Topics of interest include, but are not limited to: non-standard tensor decomposition and representation learning, deep tensor models, graph–tensor integrated learning, tensor completion and denoising, online and dynamic tensor learning, as well as emerging applications in areas such as recommender systems, intelligent transportation, and biomedical data analysis.

The goal of this session is to provide a platform for researchers and practitioners to exchange ideas, present cutting-edge results, and discuss future directions in the rapidly evolving field of tensor representation learning.

Publication:

（ISBN: 979-8-3315-8371-2）

All papers submitted to ICCEA 2026 will be reviewed by two or three expert reviewers from the conference committees. After a careful review process, all accepted papers of ICCEA 2026 will be published in IEEE Xplore and will be submitted to EI Compendex, Scopus for indexing.

Submission:

Please send the full paper(word+pdf) to Submission System.