Qi Zhu
Qi Zhu
Amazon Web Services
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Easing embedding learning by comprehensive transcription of heterogeneous information networks
Y Shi, Q Zhu, F Guo, C Zhang, J Han
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
Y Shi, H Gui, Q Zhu, L Kaplan, J Han
Proceedings of the 2018 SIAM International Conference on Data Mining, 144-152, 2018
Transfer learning of graph neural networks with ego-graph information maximization
Q Zhu, C Yang, Y Xu, H Wang, C Zhang, J Han
Advances in Neural Information Processing Systems 34, 2021
Shift-robust gnns: Overcoming the limitations of localized graph training data
Q Zhu, N Ponomareva, J Han, B Perozzi
Advances in Neural Information Processing Systems 34, 27965-27977, 2021
Heterogeneous supervision for relation extraction: A representation learning approach
L Liu, X Ren, Q Zhu, S Zhi, H Gui, H Ji, J Han
arXiv preprint arXiv:1707.00166, 2017
Can Single-Pass Contrastive Learning Work for Both Homophilic and Heterophilic Graph?
H Wang, J Zhang, Q Zhu, W Huang
Collective multi-type entity alignment between knowledge graphs
Q Zhu, H Wei, B Sisman, D Zheng, C Faloutsos, XL Dong, J Han
Proceedings of The Web Conference 2020, 2241-2252, 2020
Task-guided pair embedding in heterogeneous network
C Park, D Kim, Q Zhu, J Han, H Yu
Proceedings of the 28th ACM international conference on information and …, 2019
Unsupervised differentiable multi-aspect network embedding
C Park, C Yang, Q Zhu, D Kim, H Yu, J Han
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
Life-inet: A structured network-based knowledge exploration and analytics system for life sciences
X Ren, J Shen, M Qu, X Wang, Z Wu, Q Zhu, M Jiang, F Tao, S Sinha, ...
Proceedings of ACL 2017, System Demonstrations, 55-60, 2017
Patton: Language model pretraining on text-rich networks
B Jin, W Zhang, Y Zhang, Y Meng, X Zhang, Q Zhu, J Han
arXiv preprint arXiv:2305.12268, 2023
Heterformer: Transformer-based deep node representation learning on heterogeneous text-rich networks
B Jin, Y Zhang, Q Zhu, J Han
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
The effect of metadata on scientific literature tagging: A cross-field cross-model study
Y Zhang, B Jin, Q Zhu, Y Meng, J Han
Proceedings of the ACM Web Conference 2023, 1626-1637, 2023
Discovering hypernymy in text-rich heterogeneous information network by exploiting context granularity
Y Shi, J Shen, Y Li, N Zhang, X He, Z Lou, Q Zhu, M Walker, M Kim, J Han
Proceedings of the 28th ACM International Conference on Information and …, 2019
Facet-aware evaluation for extractive summarization
Y Mao, L Liu, Q Zhu, X Ren, J Han
arXiv preprint arXiv:1908.10383, 2019
Integrating local context and global cohesiveness for open information extraction
Q Zhu, X Ren, J Shang, Y Zhang, A El-Kishky, J Han
Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019
Expert finding in heterogeneous bibliographic networks with locally-trained embeddings
H Gui, Q Zhu, L Liu, A Zhang, J Han
arXiv preprint arXiv:1803.03370, 2018
Can GNN be Good Adapter for LLMs?
X Huang, K Han, Y Yang, D Bao, Q Tao, Z Chai, Q Zhu
arXiv preprint arXiv:2402.12984, 2024
Explaining and adapting graph conditional shift
Q Zhu, Y Jiao, N Ponomareva, J Han, B Perozzi
arXiv preprint arXiv:2306.03256, 2023
Shift-Robust Node Classification via Graph Clustering Co-training
Q Zhu, C Zhang, C Park, C Yang, J Han
NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022
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