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2021 Conference Publication CausalRec: causal inference for visual debiasing in visually-aware recommendationQiu, Ruihong, Wang, Sen, Chen, Zhi, Yin, Hongzhi and Huang, Zi (2021). CausalRec: causal inference for visual debiasing in visually-aware recommendation. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475266 |
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2021 Conference Publication Local graph convolutional networks for cross-modal hashingChen, Yudong, Wang, Sen, Lu, Jianglin, Chen, Zhi, Zhang, Zheng and Huang, Zi (2021). Local graph convolutional networks for cross-modal hashing. ACM International Conference on Multimedia, Chengdu, China (Virtual), 20-24 October 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3474085.3475346 |
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2021 Conference Publication Learning elastic embeddings for customizing on-device recommendersChen, Tong, Yin, Hongzhi, Zheng, Yujia, Huang, Zi, Wang, Yang and Wang, Meng (2021). Learning elastic embeddings for customizing on-device recommenders. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467220 |
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2021 Conference Publication Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentationLi, Yang, Chen, Tong, Luo, Yadan, Yin, Hongzhi and Huang, Zi (2021). Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, QC Canada, 19 - 27 August 2021. Palo Alto, CA United States: A A A I Press. doi: 10.24963/ijcai.2021/206 |
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2021 Conference Publication Learning to ask appropriate questions in conversational recommendationRen, Xuhui, Yin, Hongzhi, Chen, Tong, Wang, Hao, Huang, Zi and Zheng, Kai (2021). Learning to ask appropriate questions in conversational recommendation. SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, 11-15 July 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3404835.3462839 |
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2021 Conference Publication Privacy protection in deep multi-modal retrievalZhang, Peng-Fei, Li, Yang, Huang, Zi and Yin, Hongzhi (2021). Privacy protection in deep multi-modal retrieval. 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11-15 July 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462837 |
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2021 Conference Publication Graph embedding for recommendation against attribute inference attacksZhang, Shijie, Yin, Hongzhi, Chen, Tong, Huang, Zi, Cui, Lizhen and Zhang, Xiangliang (2021). Graph embedding for recommendation against attribute inference attacks. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-22 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449813 |
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2021 Conference Publication DDHH: A decentralized deep learning framework for large-scale heterogeneous networksImran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi, Zhang, Xiangliang and Zheng, Kai (2021). DDHH: A decentralized deep learning framework for large-scale heterogeneous networks. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00196 |
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2021 Conference Publication Modeling Daily Crime Events Prediction Using Seq2Seq ArchitectureAlghamdi, Jawaher and Huang, Zi (2021). Modeling Daily Crime Events Prediction Using Seq2Seq Architecture. 32nd Australasian Database Conference (ADC) Held as Part of Australasian Computer Science Week (ACSW), Online, 29 January - 5 February 2021. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-69377-0_16 |
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2021 Conference Publication Learning to diversify for single domain generalizationWang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087 |
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2021 Conference Publication Memory augmented multi-instance contrastive predictive coding for sequential recommendationQiu, Ruihong, Huang, Zi and Yin, Hongzhi (2021). Memory augmented multi-instance contrastive predictive coding for sequential recommendation. IEEE International Conference on Data Mining, Auckland, New Zealand, 7-10 December 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM51629.2021.00063 |
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2021 Conference Publication Entropy-based uncertainty calibration for generalized zero-shot learningChen, Zhi, Huang, Zi, Li, Jingjing and Zhang, Zheng (2021). Entropy-based uncertainty calibration for generalized zero-shot learning. 32nd Australasian Database Conference, ADC 2021, Dunedin, New Zealand, 29 January-5 February 2021. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-030-69377-0_12 |
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2021 Conference Publication Proactive Privacy-preserving Learning for RetrievalZhang, Peng-Fei, Huang, Zi and Xu, Xin-Shun (2021). Proactive Privacy-preserving Learning for Retrieval. 35th AAAI Conference on Artificial Intelligence, AAAI 2021, Online, 2–9 February 2021. Palo Alto, CA United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v35i4.16449 |
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2020 Conference Publication Incomplete cross-modal retrieval with dual-aligned variational autoencodersJing, Mengmeng, Li, Jingjing, Zhu, Lei, Lu, Ke, Yang, Yang and Huang, Zi (2020). Incomplete cross-modal retrieval with dual-aligned variational autoencoders. MM '20: The 28th ACM International Conference on Multimedia, Online, 12-16 October 2020. New York, NY, United States: Association for Computing Machinery, Inc. doi: 10.1145/3394171.3413676 |
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2020 Conference Publication Adversarial bipartite graph learning for video domain adaptationLuo, Yadan, Huang, Zi, Wang, Zijian, Zhang, Zheng and Baktashmotlagh, Mahsa (2020). Adversarial bipartite graph learning for video domain adaptation. ACM International Conference on Multimedia, Seattle, WA, United States, 12-16 October 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3394171.3413897 |
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2020 Conference Publication Prototype-matching graph network for heterogeneous domain adaptationWang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2020). Prototype-matching graph network for heterogeneous domain adaptation. MM '20: 28th ACM International Conference on Multimedia, Online, October 2020. New York, NY, United States: ACM. doi: 10.1145/3394171.3413662 |
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2020 Conference Publication Rethinking generative zero-shot learning: an ensemble learning perspective for recognising visual patchesChen, Zhi, Wang, Sen, Li, Jingjing and Huang, Zi (2020). Rethinking generative zero-shot learning: an ensemble learning perspective for recognising visual patches. MM '20: Proceedings of the 28th ACM International Conference on Multimedia, New York, NY USA, 12-16 October 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3394171.3413813 |
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2020 Conference Publication Completely unsupervised cross-modal hashingDuan, Jiasheng, Zhang, Pengfei and Huang, Zi (2020). Completely unsupervised cross-modal hashing. 25th International Conference on Database Systems for Advanced Applications, DASFAA 2020, Jeju, South Korea, 24 - 27 September 2020. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-59410-7_11 |
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2020 Conference Publication Try this instead: personalized and interpretable substitute recommendationChen, Tong, Yin, Hongzhi, Ye, Guanhua, Huang, Zi, Wang, Yang and Wang, Meng (2020). Try this instead: personalized and interpretable substitute recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401042 |
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2020 Conference Publication GAG: global attributed graph neural network for streaming session-based recommendationQiu, Ruihong, Yin, Hongzhi, Huang, Zi and Chen, Tong (2020). GAG: global attributed graph neural network for streaming session-based recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China , 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401109 |
