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ORCIDYingxue Zhang 0001
Person information
- affiliation: Huawei Noah's Ark Lab, Shenzhen, China
- affiliation (former): McGill University, Montreal, Canada
Other persons with the same name
- Yingxue Zhang — disambiguation page
- Yingxue Zhang 0002
![[0000-0002-0947-1875]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-0947-1875")
— Binghamton University, Binghamton, NY, USA (and 1 more) - Yingxue Zhang 0003 — Tencent Inc, Beijing, China (and 1 more)
- Yingxue Zhang 0004 — Wuhan University, Wuhan, China
- Yingxue Zhang 0005 — McGill University, Montreal, Canada
- Yingxue Zhang 0006 — Hubei Engineering University, Xiaogan, China
- Yingxue Zhang 0007 — East China University of Science and Technology, Shanghai, China
- Yingxue Zhang 0008 — Southeast University, Nanjing, Jiangsu, China
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2020 – today
- 2024
[j4]Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates:
DyG2Vec: Efficient Representation Learning for Dynamic Graphs. Trans. Mach. Learn. Res. 2024 (2024)- [j3]Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang:
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization. Trans. Mach. Learn. Res. 2024 (2024) - [j2]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. ACM Trans. Inf. Syst. 42(1): 30:1-30:27 (2024) - [c47]Mohammad Dehghan, Mohammad Ali Alomrani, Sunyam Bagga, David Alfonso-Hermelo, Khalil Bibi, Abbas Ghaddar, Yingxue Zhang, Xiaoguang Li, Jianye Hao, Qun Liu, Jimmy Lin, Boxing Chen, Prasanna Parthasarathi, Mahdi Biparva, Mehdi Rezagholizadeh:
EWEK-QA : Enhanced Web and Efficient Knowledge Graph Retrieval for Citation-based Question Answering Systems. ACL (1) 2024: 14169-14187 - [c46]Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Multi-resolution Time-Series Transformer for Long-term Forecasting. AISTATS 2024: 4222-4230 - [c45]Surya Penmetsa, Fahad Rahman Amik, Zhanguang Zhang, Yingying Fu, Yingxue Zhang, Wulong Liu, Jianye Hao:
Generalizable and Relation Sensitive Netlist Representation for Analog Circuit Design. ACM Great Lakes Symposium on VLSI 2024: 287-291 - [c44]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. ICML 2024 - [c43]Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song:
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network. KDD 2024: 1085-1095 - [c42]Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan:
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. KDD 2024: 6301-6311 - [i43]Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang:
Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization. CoRR abs/2402.05944 (2024) - [i42]Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates:
Personalized Negative Reservoir for Incremental Learning in Recommender Systems. CoRR abs/2403.03993 (2024) - [i41]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. CoRR abs/2404.13604 (2024) - [i40]Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan:
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. CoRR abs/2405.11024 (2024) - [i39]Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song:
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network. CoRR abs/2406.02651 (2024) - [i38]Mohammad Dehghan, Mohammad Ali Alomrani, Sunyam Bagga, David Alfonso-Hermelo, Khalil Bibi, Abbas Ghaddar, Yingxue Zhang, Xiaoguang Li, Jianye Hao, Qun Liu, Jimmy Lin, Boxing Chen, Prasanna Parthasarathi, Mahdi Biparva, Mehdi Rezagholizadeh:
EWEK-QA: Enhanced Web and Efficient Knowledge Graph Retrieval for Citation-based Question Answering Systems. CoRR abs/2406.10393 (2024) - [i37]Faezeh Faez, Raika Karimi, Yingxue Zhang, Xing Li, Lei Chen, Mingxuan Yuan, Mahdi Biparva:
MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization. CoRR abs/2409.06077 (2024) - [i36]Jiaming Zhou, Abbas Ghaddar, Ge Zhang, Liheng Ma, Yaochen Hu, Soumyasundar Pal, Mark Coates, Bin Wang, Yingxue Zhang, Jianye Hao:
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data. CoRR abs/2409.12437 (2024) - [i35]Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates:
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation. CoRR abs/2409.18778 (2024) - 2023
- [c41]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. AAAI 2023: 4711-4719 - [c40]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. AAAI 2023: 14400-14407 - [c39]Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates:
Spectral Augmentations for Graph Contrastive Learning. AISTATS 2023: 11213-11266 - [c38]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CIKM 2023: 741-750 - [c37]Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao:
Dual-Process Graph Neural Network for Diversified Recommendation. CIKM 2023: 2126-2135 - [c36]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. ICDE 2023: 1112-1125 - [c35]Can Chen, Yingxue Zhang, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Model-based Biological Sequence Design. ICML 2023: 5351-5366 - [c34]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. IJCAI 2023: 6656-6664 - [c33]Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang:
Hierarchical Projection Enhanced Multi-behavior Recommendation. KDD 2023: 4649-4660 - [c32]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. WWW 2023: 960-970 - [c31]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. WWW 2023: 1457-1467 - [i34]Can Chen, Yingxue Zhang, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Model-based Biological Sequence Design. CoRR abs/2301.02931 (2023) - [i33]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. CoRR abs/2301.03412 (2023) - [i32]Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates:
Spectral Augmentations for Graph Contrastive Learning. CoRR abs/2302.02909 (2023) - [i31]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. CoRR abs/2302.11087 (2023) - [i30]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. CoRR abs/2303.02418 (2023) - [i29]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. CoRR abs/2303.11700 (2023) - [i28]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. CoRR abs/2305.01204 (2023) - [i27]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CoRR abs/2308.07760 (2023) - [i26]Fuyuan Lyu, Yaochen Hu, Xing Tang, Yingxue Zhang, Ruiming Tang, Xue Liu:
Towards Automated Negative Sampling in Implicit Recommendation. CoRR abs/2311.03526 (2023) - [i25]Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Multi-resolution Time-Series Transformer for Long-term Forecasting. CoRR abs/2311.04147 (2023) - 2022
- [j1]Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates:
Node copying: A random graph model for effective graph sampling. Signal Process. 192: 108335 (2022) - [c30]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CIKM 2022: 1399-1409 - [c29]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CIKM 2022: 2148-2157 - [c28]Yunhe Li, Yaochen Hu, Yingxue Zhang:
Dual Path Graph Convolutional Networks. ICASSP 2022: 5563-5567 - [c27]Zheng Fang, Ziyun Zhang, Guojie Song, Yingxue Zhang, Dong Li, Jianye Hao, Xi Wang:
Invariant Factor Graph Neural Networks. ICDM 2022: 933-938 - [c26]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. KDD 2022: 168-178 - [c25]Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu:
Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding. KDD 2022: 2692-2702 - [c24]Can Chen, Yingxue Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates:
Bidirectional Learning for Offline Infinite-width Model-based Optimization. NeurIPS 2022 - [c23]Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao:
Versatile Multi-stage Graph Neural Network for Circuit Representation. NeurIPS 2022 - [c22]Ishaan Kumar, Yaochen Hu, Yingxue Zhang:
EFLEC: Efficient Feature-LEakage Correction in GNN based Recommendation Systems. SIGIR 2022: 1885-1889 - [c21]Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King:
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation. WSDM 2022: 94-102 - [c20]Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang:
Polarized Graph Neural Networks. WWW 2022: 1404-1413 - [i24]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. CoRR abs/2206.02115 (2022) - [i23]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CoRR abs/2208.01709 (2022) - [i22]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. CoRR abs/2208.01849 (2022) - [i21]Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates:
Node Copying: A Random Graph Model for Effective Graph Sampling. CoRR abs/2208.02435 (2022) - [i20]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CoRR abs/2208.04482 (2022) - [i19]Can Chen, Yingxue Zhang, Jie Fu, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Infinite-width Model-based Optimization. CoRR abs/2209.07507 (2022) - [i18]Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates:
DyG2Vec: Representation Learning for Dynamic Graphs with Self-Supervision. CoRR abs/2210.16906 (2022) - [i17]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. CoRR abs/2211.06370 (2022) - 2021
- [c19]Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates:
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. AAAI 2021: 4285-4293 - [c18]Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates:
Detection and Defense of Topological Adversarial Attacks on Graphs. AISTATS 2021: 2989-2997 - [c17]Kian Ahrabian, Yishi Xu, Yingxue Zhang, Jiapeng Wu, Yuening Wang, Mark Coates:
Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender Systems. CIKM 2021: 2832-2836 - [c16]Yunhe Li, Yaochen Hu, Yingxue Zhang:
Graph Representation Learning via Adversarial Variational Bayes. CIKM 2021: 3237-3241 - [c15]Yuening Wang, Yingxue Zhang, Mark Coates:
Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems. CIKM 2021: 3518-3522 - [c14]Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates:
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. ICCAD 2021: 1-9 - [c13]Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates:
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. ICML 2021: 8336-8348 - [c12]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. KDD 2021: 496-504 - [c11]Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung:
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. SIGIR 2021: 428-437 - [i16]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. CoRR abs/2101.04849 (2021) - [i15]Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates:
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. CoRR abs/2101.04852 (2021) - [i14]Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung:
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. CoRR abs/2104.08419 (2021) - [i13]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. CoRR abs/2106.00314 (2021) - [i12]Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates:
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. CoRR abs/2106.06064 (2021) - [i11]Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jian Hao, Irwin King:
Modeling Scale-free Graphs for Knowledge-aware Recommendation. CoRR abs/2108.06468 (2021) - [i10]Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He:
Content Filtering Enriched GNN Framework for News Recommendation. CoRR abs/2110.12681 (2021) - [i9]Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates:
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. CoRR abs/2111.05941 (2021) - [i8]Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King:
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation. CoRR abs/2112.01944 (2021) - 2020
- [c10]Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates:
Memory Augmented Graph Neural Networks for Sequential Recommendation. AAAI 2020: 5045-5052 - [c9]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c8]Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. ICML 2020: 8041-8050 - [c7]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. KDD 2020: 1036-1044 - [c6]Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates:
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020: 2030-2039 - [c5]Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, Mark Coates:
Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020: 1289-1298 - [c4]Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates:
Non Parametric Graph Learning for Bayesian Graph Neural Networks. UAI 2020: 1318-1327 - [i7]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i6]Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates:
Non-Parametric Graph Learning for Bayesian Graph Neural Networks. CoRR abs/2006.13335 (2020) - [i5]Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. CoRR abs/2007.05003 (2020) - [i4]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CoRR abs/2008.13517 (2020)
2010 – 2019
- 2019
- [c3]Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay:
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification. AAAI 2019: 5829-5836 - [c2]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [i3]Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates:
Memory Augmented Graph Neural Networks for Sequential Recommendation. CoRR abs/1912.11730 (2019) - 2018
- [c1]Chen Ma, Yingxue Zhang, Qinglong Wang, Xue Liu:
Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence. CIKM 2018: 697-706 - [i2]Chen Ma, Yingxue Zhang, Qinglong Wang, Xue Liu:
Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence. CoRR abs/1809.10770 (2018) - [i1]Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay:
Bayesian graph convolutional neural networks for semi-supervised classification. CoRR abs/1811.11103 (2018)
Coauthor Index
[j4] [c46] [c44] [c42] [i42] [i41] [i40] [i36] [i35] [c41] [c40] [c39] [c36] [c35] [i34] [i33] [i32] [i28] [i25] [j1] [c29] [c24] [i23] [i21] [i19] [i18] [i17] [c19] [c18] [c17] [c15] [c14] [c13] [c11] [i16] [i15] [i14] [i12] [i9] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [i7] [i6] [i5] [i4] [c3] [c2] [i3] [i1]
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