Yao Lei Xu

According to our database, Yao Lei Xu authored at least 20 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Modeling of Multiway Data on Graphs.

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

Neural Comput., August, 2023

TensorGPT: Efficient Compression of the Embedding Layer in LLMs based on the Tensor-Train Decomposition.

Mingxue Xu, Yao Lei Xu, Danilo P. Mandic

CoRR, 2023

Graph Tensor Networks: An Intuitive Framework for Designing Large-Scale Neural Learning Systems on Multiple Domains.

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

CoRR, 2023

A comparative study on ML-based approaches for Main Entity Detection in Financial Reports.

Thanos Konstantinidis, Yao Lei Xu, Tony Constantinides, Danilo P. Mandic

Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Text Mining for Sentiment Analysis in Bond Portfolio Construction.

Thanos Konstantinidis, Maya Golan, Yao Lei Xu, Tony Constantinides, Danilo P. Mandic

Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Financial News Classification Model for NLP-based Bond Portfolio Construction.

Thanos Konstantinidis, Arnau Bonet Farres, Yao Lei Xu, Tony Constantinides, Danilo P. Mandic

Proceedings of the 24th International Conference on Digital Signal Processing, 2023

Tensor Completion for Efficient and Accurate Hyperparameter Optimisation in Large-Scale Statistical Learning.

Aaman Rebello, Kriton Konstantinidis, Yao Lei Xu, Danilo P. Mandic

Proceedings of the IEEE International Conference on Acoustics, 2023

Hierarchical Graph Learning for Stock Market Prediction Via a Domain-Aware Graph Pooling Operator.

Arie N. Arya, Yao Lei Xu, Ljubisa Stankovic, Danilo P. Mandic

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Accelerating Tensor Contraction Products via Tensor-Train Decomposition [Tips & Tricks].

Ilya Kisil, Giuseppe Giovanni Calvi, Kriton Konstantinidis, Yao Lei Xu, Danilo P. Mandic

IEEE Signal Process. Mag., 2022

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Multi-Way Financial Modelling.

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

CoRR, 2022

Low-Complexity Attention Modelling via Graph Tensor Networks.

Yao Lei Xu, Kriton Konstantinidis, Shengxi Li, Ljubisa Stankovic, Danilo P. Mandic

Proceedings of the IEEE International Conference on Acoustics, 2022

Variational Bayesian Tensor Networks with Structured Posteriors.

Kriton Konstantinidis, Yao Lei Xu, Qibin Zhao, Danilo P. Mandic

Proceedings of the IEEE International Conference on Acoustics, 2022

Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books.

Jacobo Roa-Vicens, Yao Lei Xu, Ricardo Silva, Danilo P. Mandic

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021

Reducing Computational Complexity of Tensor Contractions via Tensor-Train Networks.

Ilya Kisil, Giuseppe Giovanni Calvi, Kriton Konstantinidis, Yao Lei Xu, Danilo P. Mandic

CoRR, 2021

Tensor Networks for Multi-Modal Non-Euclidean Data.

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

CoRR, 2021

Tensor-Train Recurrent Neural Networks for Interpretable Multi-Way Financial Forecasting.

Yao Lei Xu, Giuseppe Giovanni Calvi, Danilo P. Mandic

Proceedings of the International Joint Conference on Neural Networks, 2021

Graph Theory for Metro Traffic Modelling.

Bruno Scalzo Dees, Yao Lei Xu, Anthony G. Constantinides, Danilo P. Mandic

Proceedings of the International Joint Conference on Neural Networks, 2021

Recurrent Graph Tensor Networks: A Low-Complexity Framework for Modelling High-Dimensional Multi-Way Sequences.

Yao Lei Xu, Danilo P. Mandic

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Multi-Graph Tensor Networks.

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

CoRR, 2020

Recurrent Graph Tensor Networks.

Yao Lei Xu, Danilo P. Mandic

CoRR, 2020