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ORCIDTin Lok James Ng
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2020 – today
- 2024
[j3]Tin Lok James Ng, Andrew Zammit-Mangion:
Mixture modeling with normalizing flows for spherical density estimation. Adv. Data Anal. Classif. 18(1): 103-120 (2024)- 2023
- [c5]Hanyang Chen, Zhouting Zhao, Tin Lok James Ng:
Fair Machine Learning with Structured and Unstructured Features: A Case Study in Mortality Prediction. AICS 2023: 1-4 - [c4]Zhouting Zhao, Tin Lok James Ng:
Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions. ECML/PKDD (6) 2023: 460-476 - 2022
- [j2]Tin Lok James Ng, Thomas Brendan Murphy:
Model-based clustering for random hypergraphs. Adv. Data Anal. Classif. 16(3): 691-723 (2022) - 2021
- [j1]Tin Lok James Ng
, Thomas Brendan Murphy:
Model-based Clustering of Count Processes. J. Classif. 38(2): 188-211 (2021) - [i3]Weipéng Huáng, Tin Lok James Ng, Nishma Laitonjam, Neil J. Hurley:
Posterior Regularisation on Bayesian Hierarchical Mixture Clustering. CoRR abs/2105.06903 (2021) - [i2]Linyi Yang, Tin Lok James Ng, Barry Smyth, Ruihai Dong:
Fact Check: Analyzing Financial Events from Multilingual News Sources. CoRR abs/2106.15221 (2021) - 2020
- [c3]Linyi Yang, Eoin M. Kenny, Tin Lok James Ng, Yi Yang, Barry Smyth, Ruihai Dong:
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification. COLING 2020: 6150-6160 - [c2]Linyi Yang, Tin Lok James Ng, Barry Smyth, Ruihai Dong:
HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction. WWW 2020: 441-451 - [i1]Linyi Yang, Eoin M. Kenny, Tin Lok James Ng, Yi Yang, Barry Smyth, Ruihai Dong:
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification. CoRR abs/2010.12512 (2020)
2010 – 2019
- 2017
- [c1]Linyi Yang, Tin Lok James Ng, Catherine Mooney, Ruihai Dong:
Multi-level Attention-Based Neural Networks for Distant Supervised Relation Extraction. AICS 2017: 206-218
Coauthor Index
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