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2021

Conference Publication

Joint-teaching: learning to refine knowledge for resource-constrained unsupervised cross-modal retrieval

Zhang, Peng-Fei, Duan, Jiasheng, Huang, Zi and Yin, Hongzhi (2021). Joint-teaching: learning to refine knowledge for resource-constrained unsupervised cross-modal retrieval. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475286

Joint-teaching: learning to refine knowledge for resource-constrained unsupervised cross-modal retrieval

2021

Conference Publication

CausalRec: causal inference for visual debiasing in visually-aware recommendation

Qiu, 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

CausalRec: causal inference for visual debiasing in visually-aware recommendation

2021

Conference Publication

Socially-aware self-supervised tri-training for recommendation

Yu, Junliang, Yin, Hongzhi, Gao, Min, Xia, Xin, Zhang, Xiangliang and Viet Hung, Nguyen Quoc (2021). Socially-aware self-supervised tri-training for recommendation. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467340

Socially-aware self-supervised tri-training for recommendation

2021

Conference Publication

ImGAGN: imbalanced network embedding via generative adversarial graph networks

Qu, Liang, Zhu, Huaisheng, Zheng, Ruiqi, Shi, Yuhui and Yin, Hongzhi (2021). ImGAGN: imbalanced network embedding via generative adversarial graph networks. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467334

ImGAGN: imbalanced network embedding via generative adversarial graph networks

2021

Conference Publication

Learning elastic embeddings for customizing on-device recommenders

Chen, 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

Learning elastic embeddings for customizing on-device recommenders

2021

Conference Publication

Heterogeneous hypergraph embedding for graph classification

Sun, Xiangguo, Yin, Hongzhi, Liu, Bo, Chen, Hongxu, Cao, Jiuxin, Shao, Yingxia and Viet Hung, Nguyen Quoc (2021). Heterogeneous hypergraph embedding for graph classification. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event, 8-12 March 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3437963.3441835

Heterogeneous hypergraph embedding for graph classification

2021

Conference Publication

Temporal meta-path guided explainable recommendation

Chen, Hongxu, Li, Yicong, Sun, Xiangguo, Xu, Guandong and Yin, Hongzhi (2021). Temporal meta-path guided explainable recommendation. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event Israel, 8 - 12 March 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3437963.3441762

Temporal meta-path guided explainable recommendation

2021

Conference Publication

Pre-training graph neural networks for cold-start users and items representation

Hao, Bowen, Zhang, Jing, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2021). Pre-training graph neural networks for cold-start users and items representation. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event, 8-12 March 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3437963.3441738

Pre-training graph neural networks for cold-start users and items representation

2021

Conference Publication

Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation

Li, 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

Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation

2021

Conference Publication

Where are we in embedding spaces?

Zhang, Sixiao, Chen, Hongxu, Ming, Xiao, Cui, Lizhen, Yin, Hongzhi and Xu, Guandong (2021). Where are we in embedding spaces?. KDD '21: 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore, Singapore, 14 - 18 August 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3447548.3467421

Where are we in embedding spaces?

2021

Conference Publication

DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation

Guo, Lei, Tang, Li, Chen, Tong, Zhu, Lei, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2021). DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation. International Joint Conference on Artificial Intelligence, Montreal, Canada, 19-27 August 2021. San Francisco, CA, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2021/342

DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation

2021

Conference Publication

Learning to ask appropriate questions in conversational recommendation

Ren, 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

Learning to ask appropriate questions in conversational recommendation

2021

Conference Publication

Decoupling representation learning and classification for GNN-based anomaly detection

Wang, Yanling, Zhang, Jing, Guo, Shasha, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2021). Decoupling representation learning and classification for GNN-based anomaly detection. 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: 10.1145/3404835.3462944

Decoupling representation learning and classification for GNN-based anomaly detection

2021

Conference Publication

Privacy protection in deep multi-modal retrieval

Zhang, 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

Privacy protection in deep multi-modal retrieval

2021

Conference Publication

Enhancing domain-level and user-level adaptivity in diversified recommendation

Liang, Yile, Qian, Tieyun, Li, Qing and Yin, Hongzhi (2021). Enhancing domain-level and user-level adaptivity in diversified 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: 10.1145/3404835.3462957

Enhancing domain-level and user-level adaptivity in diversified recommendation

2021

Conference Publication

Self-supervised hypergraph convolutional networks for session-based recommendation

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Cui, Lizhen and Zhang, Xiangliang (2021). Self-supervised hypergraph convolutional networks for session-based recommendation. Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Virtual, 2-9 February 2021. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence.

Self-supervised hypergraph convolutional networks for session-based recommendation

2021

Conference Publication

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Cui, Lizhen and Zhang, Xiangliang (2021). Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Online, 2–9 February 2021. Washington, DC United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v35i5.16578

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

2021

Conference Publication

Adapting to context-aware knowledge in natural conversation for multi-turn response selection

Zhang, Chen, Wang, Hao, Jiang, Feijun and Yin, Hongzhi (2021). Adapting to context-aware knowledge in natural conversation for multi-turn response selection. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-23 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449902

Adapting to context-aware knowledge in natural conversation for multi-turn response selection

2021

Conference Publication

Self-supervised multi-channel hypergraph convolutional network for social recommendation

Yu, Junliang, Yin, Hongzhi, Li, Jundong, Wang, Qinyong, Hung, Nguyen Quoc Viet and Zhang, Xiangliang (2021). Self-supervised multi-channel hypergraph convolutional network for social recommendation. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-23 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449844

Self-supervised multi-channel hypergraph convolutional network for social recommendation

2021

Conference Publication

Graph embedding for recommendation against attribute inference attacks

Zhang, 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

Graph embedding for recommendation against attribute inference attacks