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ORCIDHua Mao 0001
Person information
- affiliation: Northumbria University, Department of Computer and Information Sciences, Newcastle, UK
Other persons with the same name
- Hua Mao — disambiguation page
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2020 – today
- 2025
[j30]Hui Liu, Yi Cao, Zehan Cai, Hua Mao
, Jie Chen:
Efficient algorithms for collecting the statistics of large-scale IP address data. Comput. Sci. Inf. Syst. 22(3): 927-944 (2025)- [j29]Tao Zhu, Hua Mao, Hui Liu, Jie Chen:
Progressive low-confidence pseudolabeling for semisupervised node classification. Neurocomputing 656: 131166 (2025) - [j28]Jacob Sanderson, Hua Mao, Wai Lok Woo:
GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks. IEEE Trans. Artif. Intell. 6(10): 2575-2587 (2025) - [j27]Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Zhu Wang, Xi Peng:
One-Step Adaptive Graph Learning for Incomplete Multiview Subspace Clustering. IEEE Trans. Knowl. Data Eng. 37(5): 2771-2783 (2025) - [j26]Jie Chen, Hua Mao, Yuanbiao Gou, Xi Peng:
Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams. IEEE Trans. Neural Networks Learn. Syst. 36(10): 18035-18047 (2025) - [c17]Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Xi Peng:
Cross-View Graph Consistency Learning for Invariant Graph Representations. AAAI 2025: 15795-15802 - [c16]Jacob Sanderson, Hua Mao, Wai Lok Woo:
DiPACE: Diverse, Plausible and Actionable Counterfactual Explanations. ICAART (2) 2025: 543-554 - 2024
- [j25]Seyedeh Roksana Mirzaei, Hua Mao, Raid Rafi Omar Al-Nima, Wai Lok Woo:
Explainable AI Evaluation: A Top-Down Approach for Selecting Optimal Explanations for Black Box Models. Inf. 15(1): 4 (2024) - [j24]Yuren Mao, Yu Hao, Xin Cao, Yixiang Fang, Xuemin Lin, Hua Mao, Zhiqiang Xu:
Dynamic Graph Embedding via Meta-Learning. IEEE Trans. Knowl. Data Eng. 36(7): 2967-2979 (2024) - [c15]Jacob Sanderson, Hua Mao, Naruephorn Tengtrairat, Raid Rafi Omar Al-Nima, Wai Lok Woo:
Explainable Deep Semantic Segmentation for Flood Inundation Mapping with Class Activation Mapping Techniques. ICAART (3) 2024: 1028-1035 - [i5]Jie Chen, Hua Mao, Yuanbiao Gou, Xi Peng:
Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams. CoRR abs/2409.04698 (2024) - [i4]Jie Chen, Hua Mao, Yuanbiao Gou, Zhu Wang, Xi Peng:
Self-Supervised Conditional Distribution Learning on Graphs. CoRR abs/2411.15206 (2024) - 2023
- [j23]Jacob Sanderson, Hua Mao, Mohammed A. M. Abdullah, Raid Rafi Omar Al-Nima, Wai Lok Woo:
Optimal Fusion of Multispectral Optical and SAR Images for Flood Inundation Mapping through Explainable Deep Learning. Inf. 14(12): 660 (2023) - [j22]Jie Chen, Zhu Wang, Shengxiang Yang, Hua Mao:
Two-Stage Sparse Representation Clustering for Dynamic Data Streams. IEEE Trans. Cybern. 53(10): 6408-6420 (2023) - [j21]Jie Chen, Hua Mao, Dezhong Peng, Changqing Zhang, Xi Peng:
Multiview Clustering by Consensus Spectral Rotation Fusion. IEEE Trans. Image Process. 32: 5153-5166 (2023) - [j20]Jie Chen, Zhu Wang, Hua Mao, Xi Peng:
Low-Rank Tensor Learning for Incomplete Multiview Clustering. IEEE Trans. Knowl. Data Eng. 35(11): 11556-11569 (2023) - [j19]Jie Chen, Shengxiang Yang, Zhu Wang, Hua Mao:
Efficient Sparse Representation for Learning With High-Dimensional Data. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4208-4222 (2023) - [c14]Jie Chen, Hua Mao, Wai Lok Woo, Xi Peng:
Deep Multiview Clustering by Contrasting Cluster Assignments. ICCV 2023: 16706-16715 - [i3]Jie Chen, Hua Mao, Wai Lok Woo, Xi Peng:
Deep Multiview Clustering by Contrasting Cluster Assignments. CoRR abs/2304.10769 (2023) - [i2]Jie Chen, Zhiming Li, Hua Mao, Wai Lok Woo, Xi Peng:
Cross-View Graph Consistency Learning for Invariant Graph Representations. CoRR abs/2311.11821 (2023) - 2022
- [j18]Jie Chen, Shengxiang Yang, Hua Mao, Conor Fahy:
Multiview Subspace Clustering Using Low-Rank Representation. IEEE Trans. Cybern. 52(11): 12364-12378 (2022) - [j17]Tao He, Hua Mao, Zhang Yi:
Subtraction Gates: Another Way to Learn Long-Term Dependencies in Recurrent Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1740-1751 (2022) - 2021
- [j16]Jie Chen, Hua Mao, Zhu Wang, Xinpei Zhang:
Low-rank representation with adaptive dictionary learning for subspace clustering. Knowl. Based Syst. 223: 107053 (2021) - [i1]Jie Chen, Hua Mao:
Efficient algorithms for collecting the statistics of large-scale IP address data. CoRR abs/2108.04000 (2021)
2010 – 2019
- 2019
- [j15]Yuni Zeng, Hua Mao, Dezhong Peng, Zhang Yi:
Spectrogram based multi-task audio classification. Multim. Tools Appl. 78(3): 3705-3722 (2019) - [j14]Yangxu Wang, Hua Mao, Zhang Yi:
Stem cell motion-tracking by using deep neural networks with multi-output. Neural Comput. Appl. 31(8): 3455-3467 (2019) - 2018
- [j13]Jie Chen, Hua Mao, Haixian Zhang, Zhang Yi:
Symmetric low-rank preserving projections for subspace learning. Neurocomputing 315: 381-393 (2018) - [j12]Yu Wu, Hua Mao, Zhang Yi:
Audio classification using attention-augmented convolutional neural network. Knowl. Based Syst. 161: 90-100 (2018) - 2017
- [j11]Tao He, Hua Mao, Jixiang Guo, Zhang Yi:
Cell tracking using deep neural networks with multi-task learning. Image Vis. Comput. 60: 142-153 (2017) - [j10]Yangxu Wang, Hua Mao, Zhang Yi:
Protein secondary structure prediction by using deep learning method. Knowl. Based Syst. 118: 115-123 (2017) - [j9]Jie Chen, Hua Mao, Yongsheng Sang, Zhang Yi:
Subspace clustering using a symmetric low-rank representation. Knowl. Based Syst. 127: 46-57 (2017) - [j8]Yao Zhou, Hua Mao, Zhang Yi:
Cell mitosis detection using deep neural networks. Knowl. Based Syst. 137: 19-28 (2017) - [j7]Yanan Sun, Hua Mao, Yongsheng Sang, Zhang Yi:
Explicit guiding auto-encoders for learning meaningful representation. Neural Comput. Appl. 28(3): 429-436 (2017) - [j6]Tao He, Hua Mao, Zhang Yi:
Moving object recognition using multi-view three-dimensional convolutional neural networks. Neural Comput. Appl. 28(12): 3827-3835 (2017) - [j5]Jiali Yu, Hua Mao, Zhang Yi:
Parameter as a Switch Between Dynamical States of a Network in Population Decoding. IEEE Trans. Neural Networks Learn. Syst. 28(4): 911-916 (2017) - 2016
- [j4]Jie Chen, Haixian Zhang, Hua Mao, Yongsheng Sang, Zhang Yi:
Symmetric low-rank representation for subspace clustering. Neurocomputing 173: 1192-1202 (2016) - [j3]Yifeng Zeng, Prashant Doshi, Yingke Chen, Yinghui Pan, Hua Mao, Muthukumaran Chandrasekaran:
Approximating behavioral equivalence for scaling solutions of I-DIDs. Knowl. Inf. Syst. 49(2): 511-552 (2016) - [j2]Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen:
Learning deterministic probabilistic automata from a model checking perspective. Mach. Learn. 105(2): 255-299 (2016) - [j1]Yanan Sun, Hua Mao, Quan Guo, Zhang Yi:
Learning a good representation with unsymmetrical auto-encoder. Neural Comput. Appl. 27(5): 1361-1367 (2016) - [c13]Yanan Sun, Gary G. Yen, Hua Mao, Zhang Yi:
Manifold dimension reduction based clustering for multi-objective evolutionary algorithm. CEC 2016: 3785-3792 - 2014
- [c12]Yinghui Pan, Yifeng Zeng, Hua Mao:
Learning Agents' Relations in Interactive Multiagent Dynamic Influence Diagrams. ADMI 2014: 1-11 - [c11]Wenyun Wu, Biyang Ma, Shaoxin Zhang, Yifeng Zeng, Hua Mao:
Diversifying the Storytelling Using Bayesian Networks. ADMI 2014: 104-113 - [c10]Manfred Jaeger, Hua Mao, Kim Guldstrand Larsen, Radu Mardare:
Continuity Properties of Distances for Markov Processes. QEST 2014: 297-312 - 2012
- [c9]Yifeng Zeng, Hua Mao, Yinghui Pan, Jian Luo:
Improved use of partial policies for identifying behavioral equivalence. AAMAS 2012: 1015-1022 - [c8]Yifeng Zeng, Hua Mao, Fan Yang, Jian Luo:
An Optimization Approach to Believable Behavior in Computer Games. ADMI 2012: 81-92 - [c7]Yifeng Zeng, Hua Mao, Prashant Doshi, Yinghui Pan, Jian Luo:
Learning Communication in Interactive Dynamic Influence Diagrams. IAT 2012: 243-250 - [c6]Yingke Chen, Hua Mao, Manfred Jaeger, Thomas Dyhre Nielsen, Kim Guldstrand Larsen, Brian Nielsen:
Learning Markov Models for Stationary System Behaviors. NASA Formal Methods 2012: 216-230 - [c5]Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen:
Learning Markov Decision Processes for Model Checking. QFM 2012: 49-63 - [c4]Hua Mao, Manfred Jaeger:
Learning and Model-Checking Networks of I/O Automata. ACML 2012: 285-300 - 2011
- [c3]Yifeng Zeng, Prashant Doshi, Yinghui Pan, Hua Mao, Muthukumaran Chandrasekaran, Jian Luo:
Utilizing Partial Policies for Identifying Equivalence of Behavioral Models. AAAI 2011: 1083-1088 - [c2]Yifeng Zeng, Xian He, Yanping Xiang, Hua Mao:
Dynamic Ordering-Based Search Algorithm for Markov Blanket Discovery. PAKDD (2) 2011: 420-431 - [c1]Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen:
Learning Probabilistic Automata for Model Checking. QEST 2011: 111-120
Coauthor Index
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