Dat Thanh Tran

Orcid: 0000-0002-5922-3458

According to our database1, Dat Thanh Tran authored at least 35 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Augmented bilinear network for incremental multi-stock time-series classification.
Pattern Recognit., September, 2023

Seamless Power Management for Decentralized DC Microgrid Under Voltage Sensor Faults.
IEEE Access, 2023

Cryptocurrency Portfolio Optimization by Neural Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Variational Neural Networks.
Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

Recognition of Defective Mineral Wool Using Pruned ResNet Models.
Proceedings of the 21st IEEE International Conference on Industrial Informatics, 2023

2022
Variational Neural Networks implementation in Pytorch and JAX.
Softw. Impacts, December, 2022

Efficient Design, Training, and Deployment of Artificial Neural Networks.
PhD thesis, 2022

Remote Multilinear Compressive Learning With Adaptive Compression.
IEEE Internet Things J., 2022

How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective.
CoRR, 2022

Attention-Based Neural Bag-of-Features Learning for Sequence Data.
IEEE Access, 2022

Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Multilinear Compressive Learning.
IEEE Trans. Neural Networks Learn. Syst., 2021

Bilinear Input Normalization for Neural Networks in Financial Forecasting.
CoRR, 2021

Knowledge Distillation By Sparse Representation Matching.
CoRR, 2021

2020
Heterogeneous Multilayer Generalized Operational Perceptron.
IEEE Trans. Neural Networks Learn. Syst., 2020

Progressive Operational Perceptrons with Memory.
Neurocomputing, 2020

Multilinear Compressive Learning with Prior Knowledge.
CoRR, 2020

Performance Indicator in Multilinear Compressive Learning.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Generalized Operational Classifiers for Material Identification.
Proceedings of the 22nd IEEE International Workshop on Multimedia Signal Processing, 2020

Data Normalization for Bilinear Structures in High-Frequency Financial Time-series.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Subset Sampling for Progressive Neural Network Learning.
Proceedings of the IEEE International Conference on Image Processing, 2020

2019
Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis.
IEEE Trans. Neural Networks Learn. Syst., 2019

<i>PyGOP</i>: A Python library for Generalized Operational Perceptron algorithms.
Knowl. Based Syst., 2019

Data-driven Neural Architecture Learning For Financial Time-series Forecasting.
CoRR, 2019

Knowledge Transfer for Face Verification Using Heterogeneous Generalized Operational Perceptrons.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Learning to Rank: A Progressive Neural Network Learning Approach.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Improving efficiency in convolutional neural networks with multilinear filters.
Neural Networks, 2018

Progressive Operational Perceptron with Memory.
CoRR, 2018

Heterogeneous Multilayer Generalized Operational Perceptron.
CoRR, 2018

Acceleration Approaches for Big Data Analysis.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Automatic Flower and Visitor Detection System.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Multilinear class-specific discriminant analysis.
Pattern Recognit. Lett., 2017

Improving Efficiency in Convolutional Neural Network with Multilinear Filters.
CoRR, 2017

Tensor representation in high-frequency financial data for price change prediction.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Sample-based regularization for support vector machine classification.
Proceedings of the Seventh International Conference on Image Processing Theory, 2017


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