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2020 – today
- 2024
[c82]Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang:
Mitigating Emergent Robustness Degradation while Scaling Graph Learning. ICLR 2024- [c81]Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye:
From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble. ICML 2024 - [c80]Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Chuxu Zhang, Yanfang Ye:
How to Improve Representation Alignment and Uniformity in Graph-Based Collaborative Filtering? ICWSM 2024: 1148-1159 - [c79]Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye:
Subgraph Pooling: Tackling Negative Transfer on Graphs. IJCAI 2024: 5153-5161 - [c78]Xiangchi Yuan
, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang:
Graph Cross Supervised Learning via Generalized Knowledge. KDD 2024: 4083-4094 - [c77]Zheyuan Zhang, Zehong Wang, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye:
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns. KDD 2024: 6312-6323 - [c76]Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu:
RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2024: 6749-6750 - [c75]Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Shang Ma, Chaoran Chen, Toby Li, Xusheng Xiao, Chuxu Zhang, Yanfang Ye:
Symbolic Prompt Tuning Completes the App Promotion Graph. ECML/PKDD (10) 2024: 183-198 - [c74]Yiyue Qian, Tianyi Ma, Chuxu Zhang, Yanfang Ye:
Dual-level Hypergraph Contrastive Learning with Adaptive Temperature Enhancement. WWW (Companion Volume) 2024: 859-862 - [i37]Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla:
UGMAE: A Unified Framework for Graph Masked Autoencoders. CoRR abs/2402.08023 (2024) - [i36]Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye:
Tackling Negative Transfer on Graphs. CoRR abs/2402.08907 (2024) - [i35]Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye:
Graph Inference Acceleration by Learning MLPs on Graphs without Supervision. CoRR abs/2402.08918 (2024) - [i34]Zheyuan Zhang, Zehong Wang, Shifu Hou, Evan Hall, Landon Bachman, Vincent Galassi, Jasmine White, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye:
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns. CoRR abs/2403.08820 (2024) - [i33]Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li:
Safety in Graph Machine Learning: Threats and Safeguards. CoRR abs/2405.11034 (2024) - 2023
- [j6]Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang:
Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c73]Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye:
Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning. AAAI 2023: 4383-4390 - [c72]Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang:
Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator. AAAI 2023: 4893-4901 - [c71]Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla:
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. AAAI 2023: 7793-7801 - [c70]Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla:
Heterogeneous Graph Masked Autoencoders. AAAI 2023: 9997-10005 - [c69]Chuxu Zhang:
Towards Societal Impact of AI. AAAI 2023: 15463 - [c68]Jiazheng Li, Chunhui Zhang, Chuxu Zhang:
Heterogeneous Temporal Graph Neural Network Explainer. CIKM 2023: 1298-1307 - [c67]Qianlong Wen, Jiazheng Li, Chuxu Zhang, Yanfang Ye:
A Multi-Modality Framework for Drug-Drug Interaction Prediction by Harnessing Multi-source Data. CIKM 2023: 2696-2705 - [c66]Tianyi Ma, Yiyue Qian, Chuxu Zhang, Yanfang Ye:
Hypergraph Contrastive Learning for Drug Trafficking Community Detection. ICDM 2023: 1205-1210 - [c65]Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla:
Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency. ICLR 2023 - [c64]Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang:
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. ICLR 2023 - [c63]Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang:
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization. ICLR 2023 - [c62]Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang:
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations. ICML 2023: 41133-41150 - [c61]Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla:
Graph-based Molecular Representation Learning. IJCAI 2023: 6638-6646 - [c60]Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang:
Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation. KDD 2023: 2988-2998 - [c59]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c58]Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye:
Self-Supervised Graph Structure Refinement for Graph Neural Networks. WSDM 2023: 159-167 - [c57]Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang:
Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs. WSDM 2023: 321-329 - [c56]Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang:
Fair Graph Representation Learning via Diverse Mixture-of-Experts. WWW 2023: 28-38 - [c55]Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang:
Multi-Modal Self-Supervised Learning for Recommendation. WWW 2023: 790-800 - [i32]Yijun Tian, Shichao Pei, Xiangliang Zhang, Chuxu Zhang, Nitesh V. Chawla:
Knowledge Distillation on Graphs: A Survey. CoRR abs/2302.00219 (2023) - [i31]Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang:
Multi-Modal Self-Supervised Learning for Recommendation. CoRR abs/2302.10632 (2023) - 2022
- [j5]Meng Jiang, Chuxu Zhang, Xiangliang Zhang, Neil Shah:
Editorial: Computational Behavioral Modeling for Big User Data. Frontiers Big Data 5: 893216 (2022) - [j4]Mandana Saebi, Steven Kreig, Chuxu Zhang, Meng Jiang, Tomasz Kajdanowicz, Nitesh V. Chawla:
Heterogeneous relational reasoning in knowledge graphs with reinforcement learning. Inf. Fusion 88: 12-21 (2022) - [j3]Chuxu Zhang, Julia Kiseleva, Sujay Kumar Jauhar, Ryen W. White:
Grounded Task Prioritization with Context-Aware Sequential Ranking. ACM Trans. Inf. Syst. 40(4): 68:1-68:28 (2022) - [c54]Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang:
SAIL: Self-Augmented Graph Contrastive Learning. AAAI 2022: 8927-8935 - [c53]Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang:
Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning. CIKM 2022: 1645-1654 - [c52]Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang:
A Biased Sampling Method for Imbalanced Personalized Ranking. CIKM 2022: 2393-2402 - [c51]Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang:
Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation. CIKM 2022: 2519-2528 - [c50]Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye:
Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. EMNLP (Findings) 2022: 169-181 - [c49]Jiele Wu, Chunhui Zhang, Zheyuan Liu, Erchi Zhang, Steven Wilson, Chuxu Zhang:
GraphBERT: Bridging Graph and Text for Malicious Behavior Detection on Social Media. ICDM 2022: 548-557 - [c48]Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla:
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. IJCAI 2022: 3466-3472 - [c47]Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. IJCAI 2022: 3473-3479 - [c46]Jianfei Zhang, Ai-Te Kuo, Jianan Zhao, Qianlong Wen, Erin L. Winstanley, Chuxu Zhang, Yanfang Ye:
Rx-refill Graph Neural Network to Reduce Drug Overprescribing Risks (Extended Abstract). IJCAI 2022: 5379-5383 - [c45]Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu:
Few-Shot Learning on Graphs. IJCAI 2022: 5662-5669 - [c44]Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang:
Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning. KDD 2022: 1390-1400 - [c43]Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li:
Task-Adaptive Few-shot Node Classification. KDD 2022: 1910-1919 - [c42]Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang:
Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction. KDD 2022: 2009-2019 - [c41]Lianghao Xia, Chao Huang, Chuxu Zhang:
Self-Supervised Hypergraph Transformer for Recommender Systems. KDD 2022: 2100-2109 - [c40]Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang:
Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer. KDD 2022: 2450-2460 - [c39]Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu:
Toward Graph Minimally-Supervised Learning. KDD 2022: 4782-4783 - [c38]Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang:
Co-Modality Graph Contrastive Learning for Imbalanced Node Classification. NeurIPS 2022 - [c37]Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu:
Label-invariant Augmentation for Semi-Supervised Graph Classification. NeurIPS 2022 - [c36]Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang:
HG-Meta: Graph Meta-learning over Heterogeneous Graphs. SDM 2022: 397-405 - [c35]Yujie Fan, Mingxuan Ju, Chuxu Zhang, Yanfang Ye:
Heterogeneous Temporal Graph Neural Network. SDM 2022: 657-665 - [c34]Yiming Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang:
Adapting Distilled Knowledge for Few-shot Relation Reasoning over Knowledge Graphs. SDM 2022: 666-674 - [c33]Qiang Yang, Qiannan Zhang, Chuxu Zhang, Xiangliang Zhang:
Interpretable Relation Learning on Heterogeneous Graphs. WSDM 2022: 1266-1274 - [i30]Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu:
Few-Shot Learning on Graphs: A Survey. CoRR abs/2203.09308 (2022) - [i29]Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu:
Label-invariant Augmentation for Semi-Supervised Graph Classification. CoRR abs/2205.09802 (2022) - [i28]Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks. CoRR abs/2205.12396 (2022) - [i27]Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla:
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. CoRR abs/2205.14005 (2022) - [i26]Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li:
Task-Adaptive Few-shot Node Classification. CoRR abs/2206.11972 (2022) - [i25]Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla:
Graph-based Molecular Representation Learning. CoRR abs/2207.04869 (2022) - [i24]Lianghao Xia, Chao Huang, Chuxu Zhang:
Self-Supervised Hypergraph Transformer for Recommender Systems. CoRR abs/2207.14338 (2022) - [i23]Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla:
Heterogeneous Graph Masked Autoencoders. CoRR abs/2208.09957 (2022) - [i22]Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla:
NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. CoRR abs/2208.10010 (2022) - [i21]Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang:
Adversarial Cross-View Disentangled Graph Contrastive Learning. CoRR abs/2209.07699 (2022) - [i20]Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang:
Contrastive Graph Few-Shot Learning. CoRR abs/2210.00084 (2022) - [i19]Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang:
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning. CoRR abs/2210.00162 (2022) - [i18]Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang:
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization. CoRR abs/2210.02016 (2022) - [i17]Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye:
Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering. CoRR abs/2210.02933 (2022) - [i16]Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla:
Boosting Graph Neural Networks via Adaptive Knowledge Distillation. CoRR abs/2210.05920 (2022) - [i15]Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye:
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning. CoRR abs/2211.10782 (2022) - 2021
- [j2]Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe Recommendation With Hierarchical Graph Attention Network. Frontiers Big Data 4: 778417 (2021) - [j1]Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla:
Inductive Contextual Relation Learning for Personalization. ACM Trans. Inf. Syst. 39(3): 35:1-35:22 (2021) - [c32]Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla:
Recipe Representation Learning with Networks. CIKM 2021: 1824-1833 - [c31]Jianfei Zhang, Ai-Te Kuo, Jianan Zhao, Qianlong Wen, Erin L. Winstanley, Chuxu Zhang, Yanfang Ye:
RxNet: Rx-refill Graph Neural Network for Overprescribing Detection. CIKM 2021: 2537-2546 - [c30]Yiyue Qian, Yiming Zhang, Yanfang Ye, Chuxu Zhang:
Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection. IJCAI 2021: 3684-3690 - [c29]Chuxu Zhang, Jundong Li, Meng Jiang:
Data Efficient Learning on Graphs. KDD 2021: 4092-4093 - [c28]Yiyue Qian, Yiming Zhang, Yanfang Ye, Chuxu Zhang:
Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media. NeurIPS 2021: 26911-26923 - [c27]Jianan Zhao, Qianlong Wen, Shiyu Sun, Yanfang Ye, Chuxu Zhang:
Multi-view Self-supervised Heterogeneous Graph Embedding. ECML/PKDD (2) 2021: 319-334 - [c26]Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla:
Few-Shot Graph Learning for Molecular Property Prediction. WWW 2021: 2559-2567 - [i14]Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla:
Few-Shot Graph Learning for Molecular Property Prediction. CoRR abs/2102.07916 (2021) - [i13]Yujie Fan, Mingxuan Ju, Chuxu Zhang, Liang Zhao, Yanfang Ye:
Heterogeneous Temporal Graph Neural Network. CoRR abs/2110.13889 (2021) - 2020
- [c25]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. AAAI 2020: 3041-3048 - [c24]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-Shot Learning via Knowledge Transfer. AAAI 2020: 6656-6663 - [c23]Zhichun Guo, Wenhao Yu, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla:
GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction. CIKM 2020: 435-443 - [c22]Chuxu Zhang, Lu Yu, Mandana Saebi, Meng Jiang, Nitesh V. Chawla:
Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases. EMNLP (Findings) 2020: 580-585 - [c21]Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo:
Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction. IJCAI 2020: 4359-4365 - [c20]Chuxu Zhang, Meng Jiang, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla:
Multi-modal Network Representation Learning. KDD 2020: 3557-3558 - [c19]Chuxu Zhang:
Learning from Heterogeneous Networks: Methods and Applications. WSDM 2020: 927-928 - [c18]Xian Wu, Chao Huang, Chuxu Zhang, Nitesh V. Chawla:
Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting. WWW 2020: 2320-2330 - [i12]Mandana Saebi, Steven J. Krieg, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla:
Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning. CoRR abs/2003.06050 (2020) - [i11]Lu Yu, Shichao Pei, Chuxu Zhang, Shangsong Liang, Xiao Bai, Xiangliang Zhang:
Addressing Class-Imbalance Problem in Personalized Ranking. CoRR abs/2005.09272 (2020) - [i10]Lu Yu, Shichao Pei, Chuxu Zhang, Lizhong Ding, Jun Zhou, Longfei Li, Xiangliang Zhang:
Self-supervised Smoothing Graph Neural Networks. CoRR abs/2009.00934 (2020)
2010 – 2019
- 2019
- [c17]Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla:
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data. AAAI 2019: 1409-1416 - [c16]Lu Yu, Chuxu Zhang, Shangsong Liang, Xiangliang Zhang:
Multi-Order Attentive Ranking Model for Sequential Recommendation. AAAI 2019: 5709-5716 - [c15]Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo:
Deep Dynamic Fusion Network for Traffic Accident Forecasting. CIKM 2019: 2673-2681 - [c14]Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla:
Heterogeneous Graph Neural Network. KDD 2019: 793-803 - [c13]Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla:
Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. KDD 2019: 2613-2622 - [c12]Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla:
SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks. WSDM 2019: 690-698 - [c11]Chao Huang, Chuxu Zhang, Jiashu Zhao, Xian Wu, Nitesh V. Chawla, Dawei Yin:
MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting. WWW 2019: 717-728 - [i9]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-shot Learning via Knowledge Transfer. CoRR abs/1910.03053 (2019) - [i8]Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla:
Few-Shot Knowledge Graph Completion. CoRR abs/1911.11298 (2019) - 2018
- [c10]Lu Yu, Chuxu Zhang, Shichao Pei, Guolei Sun, Xiangliang Zhang:
WalkRanker: A Unified Pairwise Ranking Model With Multiple Relations for Item Recommendation. AAAI 2018: 2596-2603 - [c9]Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla:
Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference. IJCAI 2018: 3641-3647 - [c8]Chuxu Zhang, Chao Huang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla:
Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification. WWW 2018: 709-718 - [i7]Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla:
CARL: Content-Aware Representation Learning for Heterogeneous Networks. CoRR abs/1805.04983 (2018) - [i6]Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla:
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data. CoRR abs/1811.08055 (2018) - 2017
- [c7]Chuxu Zhang, Lu Yu, Chuang Liu, Zi-Ke Zhang, Tao Zhou:
A Community-Aware Approach to Minimizing Dissemination in Graphs. APWeb/WAIM (1) 2017: 85-99 - [c6]Chuxu Zhang, Chuang Liu, Lu Yu, Zi-Ke Zhang, Tao Zhou:
Identifying the Academic Rising Stars via Pairwise Citation Increment Ranking. APWeb/WAIM (1) 2017: 475-483 - [c5]Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla:
ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation. IEEE BigData 2017: 857-866 - [c4]Chuxu Zhang, Lu Yu, Yan Wang, Chirag Shah, Xiangliang Zhang:
Collaborative User Network Embedding for Social Recommender Systems. SDM 2017: 381-389 - 2016
- [c3]Lu Yu, Ge Zhou, Chu-Xu Zhang, Junming Huang, Chuang Liu, Zi-Ke Zhang:
RankMBPR: Rank-Aware Mutual Bayesian Personalized Ranking for Item Recommendation. WAIM (1) 2016: 244-256 - [c2]Chuxu Zhang, Lu Yu, Jie Lu, Tao Zhou, Zi-Ke Zhang:
AdaWIRL: A Novel Bayesian Ranking Approach for Personal Big-Hit Paper Prediction. WAIM (2) 2016: 342-355 - [i5]Chuxu Zhang, Chuang Liu, Lu Yu, Zi-Ke Zhang, Tao Zhou:
Identifying the Academic Rising Stars. CoRR abs/1606.05752 (2016) - 2015
- [c1]Ge Zhou, Lu Yu, Chu-Xu Zhang, Chuang Liu, Zi-Ke Zhang, Jianlin Zhang:
A Novel Approach for Generating Personalized Mention List on Micro-Blogging System. ICDM Workshops 2015: 1368-1374 - 2013
- [i4]Ye Sun, Chuang Liu, Chu-Xu Zhang, Zi-Ke Zhang:
Epidemic Spreading on Weighted Complex Networks. CoRR abs/1308.4014 (2013) - [i3]Chu-Xu Zhang, Zi-Ke Zhang, Lu Yu, Chuang Liu, Hao Liu, Xiao-Yong Yan:
Information Filtering via Collaborative User Clustering Modeling. CoRR abs/1309.0691 (2013) - [i2]Zi-Ke Zhang, Chu-Xu Zhang, Xiao-Pu Han, Chuang Liu:
Emergence of Blind Areas in Information Spreading. CoRR abs/1310.4707 (2013) - 2012
- [i1]Chu-Xu Zhang, Zi-Ke Zhang, Chuang Liu:
An Evolving model of online bipartite networks. CoRR abs/1209.6217 (2012)
Coauthor Index
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
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last updated on 2024-10-21 20:33 CEST by the dblp team
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