Fan Yang
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Score-CAM: Score-weighted visual explanations for convolutional neural networks
H Wang, Z Wang, M Du, F Yang, Z Zhang, S Ding, P Mardziel, X Hu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Fairness in deep learning: A computational perspective
M Du, F Yang, N Zou, X Hu
IEEE Intelligent Systems 36 (4), 25-34, 2020
XFake: Explainable fake news detector with visualizations
F Yang, SK Pentyala, S Mohseni, M Du, H Yuan, R Linder, ED Ragan, S Ji, ...
The World Wide Web Conference, 3600-3604, 2019
An embarrassingly simple approach for trojan attack in deep neural networks
R Tang, M Du, N Liu, F Yang, X Hu
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
Evaluating explanation without ground truth in interpretable machine learning
F Yang, M Du, X Hu
arXiv preprint arXiv:1907.06831, 2019
On attribution of recurrent neural network predictions via additive decomposition
M Du, N Liu, F Yang, S Ji, X Hu
The World Wide Web Conference, 383-393, 2019
Learning credible deep neural networks with rationale regularization
M Du, N Liu, F Yang, X Hu
2019 IEEE International Conference on Data Mining (ICDM), 150-159, 2019
Towards interpretation of recommender systems with sorted explanation paths
F Yang, N Liu, S Wang, X Hu
2018 IEEE International Conference on Data Mining (ICDM), 667-676, 2018
Large-scale heterogeneous feature embedding
X Huang, Q Song, F Yang, X Hu
Proceedings of the AAAI conference on artificial intelligence 33 (01), 3878-3885, 2019
Trust evolution over time in explainable AI for fake news detection
S Mohseni, F Yang, S Pentyala, M Du, Y Liu, N Lupfer, X Hu, S Ji, ...
Fair & Responsible AI Workshop at CHI 2020, 2020
A QoE-based resource allocation scheme for multi-radio access in heterogeneous wireless network
F Yang, Q Yang, F Fu, KS Kwak
2014 14th International Symposium on Communications and Information …, 2014
Joint bandwidth and power allocation for energy efficiency optimization over heterogeneous LTE/WiFi multi-homing networks
X Zhang, F Yang
2017 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, 2017
Contextual local explanation for black box classifiers
Z Zhang, F Yang, H Wang, X Hu
arXiv preprint arXiv:1910.00768, 2019
EXACT: Scalable graph neural networks training via extreme activation compression
Z Liu, K Zhou, F Yang, L Li, R Chen, X Hu
International Conference on Learning Representations, 2021
Model-Based Counterfactual Synthesizer for Interpretation
F Yang, SS Alva, J Chen, X Hu
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
Learning credible DNNs via incorporating prior knowledge and model local explanation
M Du, N Liu, F Yang, X Hu
Knowledge and Information Systems 63 (2), 305-332, 2021
Xdeep: An interpretation tool for deep neural networks
F Yang, Z Zhang, H Wang, Y Li, X Hu
arXiv preprint arXiv:1911.01005, 2019
Generative counterfactuals for neural networks via attribute-informed perturbation
F Yang, N Liu, M Du, X Hu
ACM SIGKDD Explorations Newsletter 23 (1), 59-68, 2021
How level of explanation detail affects human performance in interpretable intelligent systems: A study on explainable fact checking
R Linder, S Mohseni, F Yang, SK Pentyala, ED Ragan, XB Hu
Applied AI Letters, e49, 2021
Machine learning explanations to prevent overtrust in fake news detection
S Mohseni, F Yang, S Pentyala, M Du, Y Liu, N Lupfer, X Hu, S Ji, ...
arXiv preprint arXiv:2007.12358, 2020
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