Yingjie Gu

Orcid: 0000-0001-9821-7483

According to our database1, Yingjie Gu authored at least 15 papers between 2013 and 2024.

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

Timeline

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Bibliography

2024
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends.
IEEE Trans. Knowl. Data Eng., March, 2024

Optimizing Large Model Training through Overlapped Activation Recomputation.
CoRR, 2024

Adapprox: Adaptive Approximation in Adam Optimization via Randomized Low-Rank Matrices.
CoRR, 2024

2022
Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

2021
Utterance-focusing multiway-matching network for dialogue-based multiple-choice machine reading comprehension.
Neurocomputing, 2021

Read, Retrospect, Select: An MRC Framework to Short Text Entity Linking.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
TT-Net: Topic Transfer-Based Neural Network for Conversational Reading Comprehension.
IEEE Access, 2019

An Empirical Evaluation on Word Embeddings Across Reading Comprehension.
Proceedings of the 11th IEEE International Conference on Advanced Infocomm Technology, 2019

2018
A Secure and Targeted Mobile Coupon Delivery Scheme Using Blockchain.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2018

2017
A Bi-Target Based Mobile Relay Selection Algorithm for MCNs.
KSII Trans. Internet Inf. Syst., 2017

2015
Active learning combining uncertainty and diversity for multi-class image classification.
IET Comput. Vis., 2015

2014
Active Learning based on Random Forest and Its Application to Terrain Classification.
Proceedings of the Progress in Systems Engineering, 2014

Combining Active Learning and Semi-supervised Learning Using Local and Global Consistency.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

Active Learning with Maximum Density and Minimum Redundancy.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

2013
Neighborhood preserving D-optimal design for active learning and its application to terrain classification.
Neural Comput. Appl., 2013


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