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2024

Sim-to-Real Global Maximum Power Point Tracking With Domain Randomization and Adaptation for Photovoltaic Systems

Wang, K., Ma, J., Man, K. L., Huang, K., & Huang, X. (2024). Sim-to-Real Global Maximum Power Point Tracking With Domain Randomization and Adaptation for Photovoltaic Systems. IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 5(3), 1143-1153. doi:10.1109/jestie.2023.3317803

DOI
10.1109/jestie.2023.3317803
Journal article

Towards Fairness-Aware Adversarial Learning

Zhang, Y., Zhang, T., Mu, R., Huang, X., & Ruan, W. (2024). Towards Fairness-Aware Adversarial Learning. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 24746-24755). IEEE. doi:10.1109/cvpr52733.2024.02337

DOI
10.1109/cvpr52733.2024.02337
Conference Paper

Scene Text Recognition via Dual-path Network with Shape-driven Attention Alignment

Hu, Y., Dong, B., Huang, K., Ding, L., Wang, W., Huang, X., & Wang, Q. -F. (2024). Scene Text Recognition via Dual-path Network with Shape-driven Attention Alignment. ACM Transactions on Multimedia Computing, Communications, and Applications, 20(4), 1-20. doi:10.1145/3633517

DOI
10.1145/3633517
Journal article

Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation

Wu, W., Dai, T., Huang, X., Ma, F., & Xiao, J. (2024). Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Vol. 33 (pp. 6175-6179). IEEE. doi:10.1109/icassp48485.2024.10447893

DOI
10.1109/icassp48485.2024.10447893
Conference Paper

Two-Stage Transfer Learning for Fusion and Classification of Airborne Hyperspectral Imagery

Rise, B., Uney, M., & Huang, X. (2024). Two-Stage Transfer Learning for Fusion and Classification of Airborne Hyperspectral Imagery. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Vol. abs/2105.07921 (pp. 6555-6559). IEEE. doi:10.1109/icassp48485.2024.10445916

DOI
10.1109/icassp48485.2024.10445916
Conference Paper

Negative Hesitation Fuzzy Sets and Their Application to Pattern Recognition

Yang, Y., Lee, S., Zhang, H., Huang, X., & Pedrycz, W. (2024). Negative Hesitation Fuzzy Sets and Their Application to Pattern Recognition. IEEE Transactions on Fuzzy Systems, 32(4), 1836-1847. doi:10.1109/tfuzz.2023.3336673

DOI
10.1109/tfuzz.2023.3336673
Journal article

Representation-Based Robustness in Goal-Conditioned Reinforcement Learning

Yin, X., Wu, S., Liu, J., Fang, M., Zhao, X., Huang, X., & Ruan, W. (n.d.). Representation-Based Robustness in Goal-Conditioned Reinforcement Learning. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 21761-21769). Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v38i19.30176

DOI
10.1609/aaai.v38i19.30176
Conference Paper

Reward Certification for Policy Smoothed Reinforcement Learning

Mu, R., Soriano Marcolino, L., Zhang, Y., Zhang, T., Huang, X., & Ruan, W. (n.d.). Reward Certification for Policy Smoothed Reinforcement Learning. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 21429-21437). Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v38i19.30139

DOI
10.1609/aaai.v38i19.30139
Conference Paper

Analysis on the Hesitation and its Application to Decision Making

Yang, Y., Lee, S., Kim, K. S., Zhang, H., Huang, X., & Pedrycz, W. (2024). Analysis on the Hesitation and its Application to Decision Making. Decision Making: Applications in Management and Engineering, 7(2), 15-34. doi:10.31181/dmame722024978

DOI
10.31181/dmame722024978
Journal article

Continuous Engineering for Trustworthy Learning-Enabled Autonomous Systems

Bensalem, S., Katsaros, P., Ničković, D., Liao, B. H. -C., Nolasco, R. R., Ahmed, M. A. E. S., . . . Wu, C. (2024). Continuous Engineering for Trustworthy Learning-Enabled Autonomous Systems. In Unknown Conference (pp. 256-278). Springer Nature Switzerland. doi:10.1007/978-3-031-46002-9_15

DOI
10.1007/978-3-031-46002-9_15
Conference Paper

DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks

Liu, J., Yi, X., & Huang, X. (2024). DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks. IEEE Transactions on Artificial Intelligence, 1-14. doi:10.1109/tai.2024.3440223

DOI
10.1109/tai.2024.3440223
Journal article

Position: Building Guardrails for Large Language Models Requires Systematic Design

Dong, Y., Mu, R., Jin, G., Qi, Y., Hu, J., Zhao, X., . . . Huang, X. (2024). Position: Building Guardrails for Large Language Models Requires Systematic Design. In Proceedings of Machine Learning Research Vol. 235 (pp. 11375-11394).

Conference Paper

Progressive Supervision for Tampering Localization in Document Images

Shao, H., Huang, K., Wang, W., Huang, X., & Wang, Q. (2024). Progressive Supervision for Tampering Localization in Document Images. In Unknown Conference (pp. 140-151). Springer Nature Singapore. doi:10.1007/978-981-99-8184-7_11

DOI
10.1007/978-981-99-8184-7_11
Conference Paper

Survey on Acceleration Techniques for Complete Neural Network Verification

Liu, Z. X., Yang, P. F., Zhang, L. J., Wu, Z. L., & Huang, X. W. (2024). Survey on Acceleration Techniques for Complete Neural Network Verification. Ruan Jian Xue Bao/Journal of Software, 35(9). doi:10.13328/j.cnki.jos.007127

DOI
10.13328/j.cnki.jos.007127
Journal article

What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety-Critical Systems

Bensalem, S., Cheng, C. -H., Huang, W., Huang, X., Wu, C., & Zhao, X. (2024). What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety-Critical Systems. In Unknown Conference (pp. 55-76). Springer Nature Switzerland. doi:10.1007/978-3-031-46002-9_4

DOI
10.1007/978-3-031-46002-9_4
Conference Paper

2023

A Symbolic Characters Aware Model for Solving Geometry Problems

Ning, M., Wang, Q. -F., Huang, K., & Huang, X. (2023). A Symbolic Characters Aware Model for Solving Geometry Problems. In Proceedings of the 31st ACM International Conference on Multimedia (pp. 7767-7775). ACM. doi:10.1145/3581783.3612570

DOI
10.1145/3581783.3612570
Conference Paper

Model Checking for Probabilistic Multiagent Systems

Fu, C., Turrini, A., Huang, X., Song, L., Feng, Y., & Zhang, L. -J. (2023). Model Checking for Probabilistic Multiagent Systems. Journal of Computer Science and Technology, 38(5), 1162-1186. doi:10.1007/s11390-022-1218-6

DOI
10.1007/s11390-022-1218-6
Journal article

An accident prediction architecture based on spatio-clock stochastic and hybrid model for autonomous driving safety

Wang, J., Huang, Z., Huang, X., Wang, T., Shen, G., & Xie, J. (2023). An accident prediction architecture based on spatio-clock stochastic and hybrid model for autonomous driving safety. In CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Vol. 35. doi:10.1002/cpe.6550

DOI
10.1002/cpe.6550
Conference Paper

Robust Bayesian Abstraction of Neural Networks

Alshareef, A., Berthier, N., Schewe, S., & Huang, X. (2023). Robust Bayesian Abstraction of Neural Networks. In 2023 International Conference on Machine Learning and Cybernetics (ICMLC) Vol. 34 (pp. 276-283). IEEE. doi:10.1109/icmlc58545.2023.10327954

DOI
10.1109/icmlc58545.2023.10327954
Conference Paper

Sora: Scalable Black-Box Reachability Analyser on Neural Networks

Xu, P., Wang, F., Ruan, W., Zhang, C., & Huang, X. (2023). Sora: Scalable Black-Box Reachability Analyser on Neural Networks. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Vol. 34 (pp. 1-5). IEEE. doi:10.1109/icassp49357.2023.10097180

DOI
10.1109/icassp49357.2023.10097180
Conference Paper

Generalizing universal adversarial perturbations for deep neural networks

Zhang, Y., Ruan, W., Wang, F., & Huang, X. (2023). Generalizing universal adversarial perturbations for deep neural networks. MACHINE LEARNING, 112(5), 1597-1626. doi:10.1007/s10994-023-06306-z

DOI
10.1007/s10994-023-06306-z
Journal article

Machine Learning Safety

Huang, X., Jin, G., & Ruan, W. (2023). Machine Learning Safety. Springer Nature Singapore. doi:10.1007/978-981-19-6814-3

DOI
10.1007/978-981-19-6814-3
Book

Model-Agnostic Reachability Analysis on Deep Neural Networks

Zhang, C., Ruan, W., Wang, F., Xu, P., Min, G., & Huang, X. (2023). Model-Agnostic Reachability Analysis on Deep Neural Networks. In Unknown Conference (pp. 341-354). Springer Nature Switzerland. doi:10.1007/978-3-031-33374-3_27

DOI
10.1007/978-3-031-33374-3_27
Conference Paper

The IJCAI-23 Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning (AISafety-SafeRL2023)

Pedroza, G., Chen, X. C., Hernández-Orallo, J., Huang, X., Theodorou, A., Matragkas, N., . . . Liu, A. (2023). The IJCAI-23 Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning (AISafety-SafeRL2023). In CEUR Workshop Proceedings Vol. 3505.

Conference Paper

2022

Multi-Scope Feature Extraction for Point Cloud Completion

Ma, W., Wang, Q. -F., Huang, K., & Huang, X. (2022). Multi-Scope Feature Extraction for Point Cloud Completion. In 2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) (pp. 727-732). IEEE. doi:10.1109/iccsi55536.2022.9970616

DOI
10.1109/iccsi55536.2022.9970616
Conference Paper

Editorial to theme section on open environmental software systems modeling

Yue, T., Arcaini, P., Wu, J., & Huang, X. (2022). Editorial to theme section on open environmental software systems modeling. SOFTWARE AND SYSTEMS MODELING, 21(4), 1273-1275. doi:10.1007/s10270-022-01032-x

DOI
10.1007/s10270-022-01032-x
Journal article

Soft pseudo-Label shrinkage for unsupervised domain adaptive person re-identification

Zheng, D., Xiao, J., Chen, K., Huang, X., Chen, L., & Zhao, Y. (2022). Soft pseudo-Label shrinkage for unsupervised domain adaptive person re-identification. PATTERN RECOGNITION, 127. doi:10.1016/j.patcog.2022.108615

DOI
10.1016/j.patcog.2022.108615
Journal article

A Graph Neural Network Reasoner for Game Description Language

Gunawan, A., Ruan, J., & Huang, X. (2022). A Graph Neural Network Reasoner for Game Description Language. In Proceedings of the Nineteenth International Conference on Principles of Knowledge Representation and Reasoning (pp. 443-452). International Joint Conferences on Artificial Intelligence Organization. doi:10.24963/kr.2022/46

DOI
10.24963/kr.2022/46
Conference Paper

A Graph Neural Network Reasoner for Game Description Language

Gunawan, A., Ruan, J., & Huang, X. (2022). A Graph Neural Network Reasoner for Game Description Language. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS Vol. 3 (pp. 1607-1609).

Conference Paper

Bridging Formal Methods and Machine Learning with Global Optimisation

Huang, X., Ruan, W., Tang, Q., & Zhao, X. (2022). Bridging Formal Methods and Machine Learning with Global Optimisation. In Lecture Notes in Computer Science (pp. 1-19). Springer International Publishing. doi:10.1007/978-3-031-17244-1_1

DOI
10.1007/978-3-031-17244-1_1
Chapter

The AAAI-22 Workshop on Artificial Intelligence Safety (SafeAI 2022)

Pedroza, G., Hernández-Orallo, J., Chen, X. C., Huang, X., Espinoza, H., Castillo-Effen, M., . . . ÓhÉigeartaigh, S. S. (2022). The AAAI-22 Workshop on Artificial Intelligence Safety (SafeAI 2022). In CEUR Workshop Proceedings Vol. 3087.

Conference Paper

The IJCAI-ECAI-22 Workshop on Artificial Intelligence Safety

Pedroza, G., Chen, X. C., Hernández-Orallo, J., Huang, X., Espinoza, H., Mallah, R., . . . Castillo-Effen, M. (2022). The IJCAI-ECAI-22 Workshop on Artificial Intelligence Safety. In CEUR Workshop Proceedings Vol. 3215.

Conference Paper

2021

Spatio-Clock Synchronous Constraint Guided Safe Reinforcement Learning for Autonomous Driving

Wang, J., Huang, Z., Yang, D., Huang, X., Zhu, Y., & Hua, G. (2021). Spatio-Clock Synchronous Constraint Guided Safe Reinforcement Learning for Autonomous Driving. Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 58(12), 2585-2603. doi:10.7544/issn1000-1239.2021.20211023

DOI
10.7544/issn1000-1239.2021.20211023
Journal article

Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance

DOI
10.48550/arxiv.2112.00646
Preprint

Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications

Ruan, W., Yi, X., & Huang, X. (2021). Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 4866-4869). ACM. doi:10.1145/3459637.3482029

DOI
10.1145/3459637.3482029
Conference Paper

Sim-to-Real Deep Reinforcement Learning for Maximum Power Point Tracking of Photovoltaic Systems

Wang, K., Ma, J., Man, K. L., Huang, K., & Huang, X. (2021). Sim-to-Real Deep Reinforcement Learning for Maximum Power Point Tracking of Photovoltaic Systems. In 2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE). doi:10.1109/EEEIC/ICPSEurope51590.2021.9584821

DOI
10.1109/EEEIC/ICPSEurope51590.2021.9584821
Conference Paper

Sim-to-Real Transfer with Domain Randomization for Maximum Power Point Estimation of Photovoltaic Systems

Wang, K., Ma, J., Man, K. L., Huang, K., & Huang, X. (2021). Sim-to-Real Transfer with Domain Randomization for Maximum Power Point Estimation of Photovoltaic Systems. In 2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE). doi:10.1109/EEEIC/ICPSEurope51590.2021.9584526

DOI
10.1109/EEEIC/ICPSEurope51590.2021.9584526
Conference Paper

A Segment-Based Layout Aware Model for Information Extraction on Document Images

Ning, M., Wang, Q. -F., Huang, K., & Huang, X. (2021). A Segment-Based Layout Aware Model for Information Extraction on Document Images. In Unknown Conference (pp. 757-765). Springer International Publishing. doi:10.1007/978-3-030-92307-5_88

DOI
10.1007/978-3-030-92307-5_88
Conference Paper

BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation

Meng, Y., Zhang, H., Gao, D., Zhao, Y., Yang, X., Qian, X., . . . Zheng, Y. (2021). BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation. In 32nd British Machine Vision Conference, BMVC 2021.

Conference Paper

Statistical Certification of Acceptable Robustness for Neural Networks

Huang, C., Hu, Z., Huang, X., & Pei, K. (2021). Statistical Certification of Acceptable Robustness for Neural Networks. In Unknown Conference (pp. 79-90). Springer International Publishing. doi:10.1007/978-3-030-86362-3_7

DOI
10.1007/978-3-030-86362-3_7
Conference Paper

The AAAI-21 workshop on artificial intelligence safety (safeai 2021)

Espinoza, H., Hernández-Orallo, J., Chen, X. C., ÓhÉigeartaigh, S. S., Huang, X., Castillo-Effen, M., . . . McDermid, J. (2021). The AAAI-21 workshop on artificial intelligence safety (safeai 2021). In CEUR Workshop Proceedings Vol. 2808.

Conference Paper

The IJCAI-21 Workshop on Artificial Intelligence Safety (AISafety2021)

Espinoza, H., Pedroza, G., Hernández-Orallo, J., Chen, X. C., ÓhÉigeartaigh, S. S., Huang, X., . . . McDermid, J. (2021). The IJCAI-21 Workshop on Artificial Intelligence Safety (AISafety2021). In CEUR Workshop Proceedings Vol. 2916.

Conference Paper

2020

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program

Bang, G., Barash, G., Bea, R., Cali, J., Castillo-Effen, M., Chen, X. C., . . . Zhang, J. (2020). The Association for the Advancement of Artificial Intelligence 2020 Workshop Program. AI MAGAZINE, 41(4), 100-114. Retrieved from https://www.webofscience.com/

Journal article

PRODeep: a platform for robustness verification of deep neural networks

Li, R., Li, J., Huang, C. -C., Yang, P., Huang, X., Zhang, L., . . . Hermanns, H. (2020). PRODeep: a platform for robustness verification of deep neural networks. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering Vol. 11822 (pp. 1630-1634). ACM. doi:10.1145/3368089.3417918

DOI
10.1145/3368089.3417918
Conference Paper

A Safety Framework for Critical Systems Utilising Deep Neural Networks

Zhao, X., Banks, A., Sharp, J., Robu, V., Flynn, D., Fisher, M., & Huang, X. (2020). A Safety Framework for Critical Systems Utilising Deep Neural Networks. In Computer Safety, Reliability, and Security (Vol. 12234, pp. 244-259). Springer Nature. doi:10.1007/978-3-030-54549-9_16

DOI
10.1007/978-3-030-54549-9_16
Chapter

Explaining Image Classifiers Using Statistical Fault Localization

Sun, Y., Chockler, H., Huang, X., & Kroening, D. (2020). Explaining Image Classifiers Using Statistical Fault Localization. In Computer Vision – ECCV 2020 (Vol. 12373, pp. 391-406). Springer Nature. doi:10.1007/978-3-030-58604-1_24

DOI
10.1007/978-3-030-58604-1_24
Chapter

The AAAI-20 workshop on artificial intelligence safety (SafeAI 2020)

Espinoza, H., Hernández-Orallo, J., Chen, X. C., ÓhÉigeartaigh, S. S., Huang, X., Castillo-Effen, M., . . . McDermid, J. (2020). The AAAI-20 workshop on artificial intelligence safety (SafeAI 2020). In CEUR Workshop Proceedings Vol. 2560 (pp. I-IV).

Conference Paper

The IJCAI-PRICAI-20 workshop on artificial intelligence safety (AISafety 2020)

Espinoza, H., McDermid, J., Huang, X., Castillo-Effen, M., Chen, X. C., Hernández-Orallo, J., . . . Mallah, R. (2020). The IJCAI-PRICAI-20 workshop on artificial intelligence safety (AISafety 2020). In CEUR Workshop Proceedings Vol. 2640.

Conference Paper

2019

Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles

Wu, M., Louw, T., Lahijanian, M., Ruan, W., Huang, X., Merat, N., & Kwiatkowska, M. (2019). Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles. In 2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 6210-6216). doi:10.1109/iros40897.2019.8967779

DOI
10.1109/iros40897.2019.8967779
Conference Paper

Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management

DOI
10.48550/arxiv.1909.03019
Preprint

Reasoning about Cognitive Trust in Stochastic Multiagent Systems

Huang, X., & Kwiatkowska, M. (2017). Reasoning about Cognitive Trust in Stochastic Multiagent Systems. In THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 3768-3774). Retrieved from https://www.webofscience.com/

Conference Paper

DeepConcolic: Testing and Debugging Deep Neural Networks

Sun, Y., Huang, X., Kroening, D., Sharp, J., Hill, M., & Ashmore, R. (2019). DeepConcolic: Testing and Debugging Deep Neural Networks. In 2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: COMPANION PROCEEDINGS (ICSE-COMPANION 2019) (pp. 111-114). doi:10.1109/ICSE-Companion.2019.00051

DOI
10.1109/ICSE-Companion.2019.00051
Conference Paper

Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification

Li, J., Liu, J., Yang, P., Chen, L., Huang, X., & Zhang, L. (2019). Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification. In Unknown Conference (pp. 296-319). Springer International Publishing. doi:10.1007/978-3-030-32304-2_15

DOI
10.1007/978-3-030-32304-2_15
Conference Paper

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

Barash, G., Castillo-Effen, M., Chhaya, N., Clark, P., Espinoza, H., Farchi, E., . . . Zitouni, I. (2019). Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. In AI MAGAZINE Vol. 40 (pp. 67-78). doi:10.1609/aimag.v40i3.4981

DOI
10.1609/aimag.v40i3.4981
Conference Paper

The AAAI-19 workshop on artificial intelligence safety (SafeAI 2019)

Espinoza, H., hÉigeartaigh, S., Huang, X., Hernández-Orallo, J., & Castillo-Effen, M. (2019). The AAAI-19 workshop on artificial intelligence safety (SafeAI 2019). In CEUR Workshop Proceedings Vol. 2301.

Conference Paper

The IJCAI-19 workshop on artificial intelligence safety (AI Safety 2019)

Espinoza, H., Yu, H., Huang, X., Lecue, F., Chen, C., Hernández-Orallo, J., . . . Mallah, R. (2019). The IJCAI-19 workshop on artificial intelligence safety (AI Safety 2019). In CEUR Workshop Proceedings Vol. 2419.

Conference Paper

Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management.

Zhao, X., Osborne, M., Lantair, J., Robu, V., Flynn, D., Huang, X., . . . Ferrando, A. (2019). Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management.. In P. C. Ölveczky, & G. Salaün (Eds.), SEFM Vol. 11724 (pp. 105-124). Springer. Retrieved from https://doi.org/10.1007/978-3-030-30446-1

Conference Paper

2018

A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability

DOI
10.48550/arxiv.1812.08342
Preprint

An Epistemic Strategy Logic

Huang, X., & Meyden, R. V. D. (2018). An Epistemic Strategy Logic. ACM Transactions on Computational Logic, 19(4). doi:10.1145/3233769

DOI
10.1145/3233769
Journal article

A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees

DOI
10.48550/arxiv.1807.03571
Preprint

Concolic Testing for Deep Neural Networks

Sun, Y., Wu, M., Ruan, W., Huang, X., Kwiatkowska, M., & Kroening, D. (2018, September 3). Concolic Testing for Deep Neural Networks. In 33rd IEEE/ACM International Conference on Automated Software Engineering. Montpellier, France. Retrieved from http://arxiv.org/abs/1805.00089v1

Conference Paper

Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm

DOI
10.48550/arxiv.1804.05805
Preprint

Testing Deep Neural Networks

Sun, Y., Huang, X., Kroening, D., Sharp, J., Hill, M., & Ashmore, R. (2018). Testing Deep Neural Networks. Retrieved from http://arxiv.org/abs/1803.04792v4

Journal article

Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems

Fu, C., Turrini, A., Huang, X., Song, L., Feng, Y., & Zhang, L. (2018). Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems. In PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 4757-4763). Retrieved from https://www.webofscience.com/

Conference Paper

Reachability Analysis of Deep Neural Networks with Provable Guarantees

Ruan, W., Huang, X., & Kwiatkowska, M. (2018). Reachability Analysis of Deep Neural Networks with Provable Guarantees. In PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 2651-2659). Retrieved from https://www.webofscience.com/

Conference Paper

2017

ATL Strategic Reasoning Meets Correlated Equilibrium

Huang, X., & Ruan, J. (2017). ATL Strategic Reasoning Meets Correlated Equilibrium. In PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 1102-1108). Retrieved from https://www.webofscience.com/

Conference Paper

Quantified Coalition Logic of Knowledge, Belief and Certainty

Chen, Q., Huang, X., Su, K., & Sattar, A. (2017). Quantified Coalition Logic of Knowledge, Belief and Certainty. In ADVANCES IN ARTIFICIAL INTELLIGENCE, CANADIAN AI 2017 Vol. 10233 (pp. 351-360). doi:10.1007/978-3-319-57351-9_40

DOI
10.1007/978-3-319-57351-9_40
Conference Paper

Reasoning about cognitive trust in stochastic multiagent systems

Huang, X., & Kwiatkowska, M. (2017). Reasoning about cognitive trust in stochastic multiagent systems. In 31st AAAI Conference on Artificial Intelligence, AAAI 2017 (pp. 3768-3774).

Conference Paper

2016

The complexity of approximations for epistemic synthesis (extended abstract)

Huang, X., & van der Meyden, R. (n.d.). The complexity of approximations for epistemic synthesis (extended abstract). In Electronic Proceedings in Theoretical Computer Science Vol. 202 (pp. 120-137). Open Publishing Association. doi:10.4204/eptcs.202.9

DOI
10.4204/eptcs.202.9
Conference Paper

Model checking probabilistic knowledge: A PSPACE case

Huang, X., & Kwiatkowska, M. (2016). Model checking probabilistic knowledge: A PSPACE case. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016 (pp. 2516-2522).

Conference Paper

Normative multiagent systems: A dynamic generalization

Huang, X., Ruan, J., Chen, Q., & Su, K. (2016). Normative multiagent systems: A dynamic generalization. IJCAI International Joint Conference on Artificial Intelligence, 2016-January, 1123-1129.

Journal article

Reconfigurability in reactive multiagent systems

Huang, X., Chen, Q., Meng, J., & Su, K. (2016). Reconfigurability in reactive multiagent systems. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2016-January (pp. 315-321).

Conference Paper

Safety Verification of Deep Neural Networks

Huang, X., Kwiatkowska, M., Wang, S., & Wu, M. (2016). Safety Verification of Deep Neural Networks. CoRR, abs/1610.06940. Retrieved from http://arxiv.org/abs/1610.06940

Journal article

Strengthening agents strategic ability with communication

Huang, X., Chen, Q., & Su, K. (2016). Strengthening agents strategic ability with communication. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016 (pp. 2509-2515).

Conference Paper

2015

Bounded model checking of strategy ability with perfect recall

Huang, X. (2015). Bounded model checking of strategy ability with perfect recall. Artificial Intelligence, 222, 182-200. doi:10.1016/j.artint.2015.01.005

DOI
10.1016/j.artint.2015.01.005
Journal article

The Complexity of Model Checking Succinct Multiagent Systems

Huang, X., Chen, Q., & Su, K. (2015). The Complexity of Model Checking Succinct Multiagent Systems. In PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI) (pp. 1076-1082). Retrieved from https://www.webofscience.com/

Conference Paper

2014

An Epistemic Strategy Logic

Huang, X., & Meyden, R. V. D. (2014). An Epistemic Strategy Logic. Retrieved from http://arxiv.org/abs/1409.2193v3

Journal article

An Epistemic Strategy Logic (Extended Abstract)

Huang, X., & van der Meyden, R. (n.d.). An Epistemic Strategy Logic (Extended Abstract). In Electronic Proceedings in Theoretical Computer Science Vol. 146 (pp. 35-41). Open Publishing Association. doi:10.4204/eptcs.146.5

DOI
10.4204/eptcs.146.5
Conference Paper

A Temporal Logic of Strategic Knowledge

Huang, X., & van der Meyden, R. (2014). A Temporal Logic of Strategic Knowledge. In FOURTEENTH INTERNATIONAL CONFERENCE ON THE PRINCIPLES OF KNOWLEDGE REPRESENTATION AND REASONING (pp. 418-427). Retrieved from https://www.webofscience.com/

Conference Paper

Symbolic Model Checking Epistemic Strategy Logic

Huang, X., & Van der Meyden, R. (2014). Symbolic Model Checking Epistemic Strategy Logic. In PROCEEDINGS OF THE TWENTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (pp. 1426-1432). Retrieved from https://www.webofscience.com/

Conference Paper

Symbolic Synthesis for Epistemic Specifications with Observational Semantics

Huang, X., & van der Meyden, R. (2014). Symbolic Synthesis for Epistemic Specifications with Observational Semantics. In Unknown Conference (pp. 455-469). Springer Berlin Heidelberg. doi:10.1007/978-3-642-54862-8_39

DOI
10.1007/978-3-642-54862-8_39
Conference Paper

2013

Model Checking for Reasoning about Incomplete Information Games

Huang, X., Ruan, J., & Thielscher, M. (2013). Model Checking for Reasoning about Incomplete Information Games. In Unknown Conference (pp. 246-258). Springer International Publishing. doi:10.1007/978-3-319-03680-9_27

DOI
10.1007/978-3-319-03680-9_27
Conference Paper

A logic of probabilistic knowledge and strategy

Huang, X., & Luo, C. (2013). A logic of probabilistic knowledge and strategy. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 845-852).

Conference Paper

Bounded planning for strategic goals with incomplete information and perfect recall

Huang, X. (2013). Bounded planning for strategic goals with incomplete information and perfect recall. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 885-892).

Conference Paper

Diagnosability in concurrent probabilistic systems

Huang, X. (2013). Diagnosability in concurrent probabilistic systems. In 12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 Vol. 2 (pp. 853-860).

Conference Paper

Symbolic synthesis of knowledge-based program implementations with synchronous semantics

Huang, X., & Van Der Meyden, R. (2013). Symbolic synthesis of knowledge-based program implementations with synchronous semantics. Proceedings of the 14th Conference on Theoretical Aspects of Rationality and Knowledge, TARK 2013, 121-130.

Journal article

2012

Probabilistic alternating-time temporal logic of incomplete information and synchronous perfect recall

Huang, X., Su, K., & Zhang, C. (2012). Probabilistic alternating-time temporal logic of incomplete information and synchronous perfect recall. In Proceedings of the National Conference on Artificial Intelligence Vol. 1 (pp. 765-771).

Conference Paper

Synthesizing strategies for epistemic goals by epistemic model checking: An application to pursuit evasion games

Huang, X., & Van Der Meyden, R. (2012). Synthesizing strategies for epistemic goals by epistemic model checking: An application to pursuit evasion games. In Proceedings of the National Conference on Artificial Intelligence Vol. 1 (pp. 772-778).

Conference Paper

Probabilistic Alternating-Time Temporal Logic of Incomplete Information and Synchronous Perfect Recall

Huang, X., Su, K., & Zhang, C. (2012). Probabilistic Alternating-Time Temporal Logic of Incomplete Information and Synchronous Perfect Recall. In Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012 (pp. 765-771).

Conference Paper

Synthesizing Strategies for Epistemic Goals by Epistemic Model Checking: An Application to Pursuit Evasion Games

Huang, X., & van der Meyden, R. (2012). Synthesizing Strategies for Epistemic Goals by Epistemic Model Checking: An Application to Pursuit Evasion Games. In Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012 (pp. 772-778).

Conference Paper

2011

Model checking knowledge in pursuit evasion games

Huang, X., Maupin, P., & Van Der Meyden, R. (2011). Model checking knowledge in pursuit evasion games. In IJCAI International Joint Conference on Artificial Intelligence (pp. 240-245). doi:10.5591/978-1-57735-516-8/IJCAI11-051

DOI
10.5591/978-1-57735-516-8/IJCAI11-051
Conference Paper

Symbolic model checking of probabilistic knowledge

Huang, X., Luo, C., & van der Meyden, R. (2011). Symbolic model checking of probabilistic knowledge. In Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge Vol. 3308 (pp. 177-186). ACM. doi:10.1145/2000378.2000399

DOI
10.1145/2000378.2000399
Conference Paper

Improved Bounded Model Checking for a Fair Branching-Time Temporal Epistemic Logic

Huang, X., Luo, C., & van der Meyden, R. (2011). Improved Bounded Model Checking for a Fair Branching-Time Temporal Epistemic Logic. In Unknown Conference (pp. 95-111). Springer Berlin Heidelberg. doi:10.1007/978-3-642-20674-0_7

DOI
10.1007/978-3-642-20674-0_7
Conference Paper

2010

A precongruence format for should testing preorder

Huang, X., Jiao, L., & Lu, W. (2010). A precongruence format for should testing preorder. JOURNAL OF LOGIC AND ALGEBRAIC PROGRAMMING, 79(3-5), 245-263. doi:10.1016/j.jlap.2010.03.001

DOI
10.1016/j.jlap.2010.03.001
Journal article

Congruence Formats for Weak Readiness Equivalence and Weak Possible Future Equivalence

Huang, X., Jiao, L., & Lu, W. (2010). Congruence Formats for Weak Readiness Equivalence and Weak Possible Future Equivalence. COMPUTER JOURNAL, 53(1), 21-36. doi:10.1093/comjnl/bxn009

DOI
10.1093/comjnl/bxn009
Journal article

Improved bounded model checking for a fair branching-time temporal epistemic logic

Huang, X., Luo, C., & Meyden, R. V. D. (2010). Improved bounded model checking for a fair branching-time temporal epistemic logic. In 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3 (pp. 1403-1404). doi:10.1145/1838206.1838403

DOI
10.1145/1838206.1838403
Conference Paper

The complexity of epistemic model checking: Clock semantics and branching time

Huang, X., & Van Der Meyden, R. (2010). The complexity of epistemic model checking: Clock semantics and branching time. In Frontiers in Artificial Intelligence and Applications Vol. 215 (pp. 549-554). doi:10.3233/978-1-60750-606-5-549

DOI
10.3233/978-1-60750-606-5-549
Conference Paper

2009

Model Checking Games for a Fair Branching-Time Temporal Epistemic Logic

Huang, X., & van der Meyden, R. (2009). Model Checking Games for a Fair Branching-Time Temporal Epistemic Logic. In Unknown Conference (pp. 11-20). Springer Berlin Heidelberg. doi:10.1007/978-3-642-10439-8_2

DOI
10.1007/978-3-642-10439-8_2
Conference Paper

2008

Weak Parametric Failure Equivalences and Their Congruence Formats

Huang, X., Jiao, L., & Lu, W. (2008). Weak Parametric Failure Equivalences and Their Congruence Formats. In Theory of Computing 2008. Proc. Fourteenth Computing: The Australasian Theory Symposium (CATS 2008), Wollongong, NSW, Australia, January 22-25, 2008. Proceedings (pp. 15-26). Retrieved from http://crpit.com/abstracts/CRPITV77Huang.html

Conference Paper

2007

A Semantic Preorder on Refinement and Fairness

Huang, X. W., Jiao, L., & Lu, W. M. (2007). A Semantic Preorder on Refinement and Fairness. In First Joint IEEE/IFIP Symposium on Theoretical Aspects of Software Engineering (TASE '07) Vol. 31 (pp. 139-148). IEEE. doi:10.1109/tase.2007.5

DOI
10.1109/tase.2007.5
Conference Paper

A Modular Petri Net Used in Synchronous Communication of Sequential Processes

Huang, X., & Meng, J. (2007). A Modular Petri Net Used in Synchronous Communication of Sequential Processes. In Proceedings of the 2007 International Conference on Modeling, Simulation & Visualization Methods, MSV 2007, Las Vegas, Nevada, USA, June 25-28, 2007 (pp. 194-200).

Conference Paper

A Semantic Preorder Combining ST Notion and Fair Testing Semantic

Huang, X., & Meng, J. (2007). A Semantic Preorder Combining ST Notion and Fair Testing Semantic. In Proceedings of the 2007 International Conference on Foundations of Computer Science, FCS 2007, June 25-28, 2007, Las Vegas, Nevada, USA (pp. 82-88).

Conference Paper

What Semantic Equivalences Are Suitable for Non-interference Properties in Computer Security

Huang, X., Jiao, L., & Lu, W. (2007). What Semantic Equivalences Are Suitable for Non-interference Properties in Computer Security. In Unknown Conference (pp. 334-349). Springer Berlin Heidelberg. doi:10.1007/978-3-540-77048-0_26

DOI
10.1007/978-3-540-77048-0_26
Conference Paper