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2020 – today
- 2024
[j38]Yakun Chen
, Ruotong Hu, Zihao Li, Chao Yang, Xianzhi Wang, Guodong Long, Guandong Xu:
Exploring explicit and implicit graph learning for multivariate time series imputation. Eng. Appl. Artif. Intell. 127(Part A): 107217 (2024)- [j37]Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu:
Dyformer: A dynamic transformer-based architecture for multivariate time series classification. Inf. Sci. 656: 119881 (2024) - [j36]Xiaojun Chen, Ting Liu, Philippe Fournier-Viger, Bowen Zhang, Guodong Long, Qin Zhang:
A fine-grained self-adapting prompt learning approach for few-shot learning with pre-trained language models. Knowl. Based Syst. 299: 111968 (2024) - [j35]Shaoxiong Ji, Yue Tan, Teemu Saravirta, Zhiqin Yang, Yixin Liu, Lauri Vasankari, Shirui Pan, Guodong Long, Anwar Walid:
Emerging trends in federated learning: from model fusion to federated X learning. Int. J. Mach. Learn. Cybern. 15(9): 3769-3790 (2024) - [j34]Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis:
TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2003-2013 (2024) - [c123]Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Jianbing Shen, Guodong Long, Can Xu, Daxin Jiang:
Fine-Grained Distillation for Long Document Retrieval. AAAI 2024: 19732-19740 - [c122]Jiazhan Feng, Chongyang Tao, Xiubo Geng, Tao Shen, Can Xu, Guodong Long, Dongyan Zhao, Daxin Jiang:
Synergistic Interplay between Search and Large Language Models for Information Retrieval. ACL (1) 2024: 9571-9583 - [c121]Tao Shen, Guodong Long, Xiubo Geng, Chongyang Tao, Yibin Lei, Tianyi Zhou, Michael Blumenstein, Daxin Jiang:
Retrieval-Augmented Retrieval: Large Language Models are Strong Zero-Shot Retriever. ACL (Findings) 2024: 15933-15946 - [c120]Yiyuan Yang, Guodong Long, Michael Blumenstein, Xiubo Geng, Chongyang Tao, Tao Shen, Daxin Jiang:
Pre-training Cross-Modal Retrieval by Expansive Lexicon-Patch Alignment. LREC/COLING 2024: 12977-12987 - [c119]Yang Li, Canran Xu, Guodong Long, Tao Shen, Chongyang Tao, Jing Jiang:
CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification. EACL (1) 2024: 2977-2988 - [c118]Zhiwei Li, Guodong Long, Tianyi Zhou:
Federated Recommendation with Additive Personalization. ICLR 2024 - [c117]Peng Yan, Guodong Long:
Client-Supervised Federated Learning: Towards One-Model-for-All Personalization. ICME 2024: 1-6 - [c116]Jiale Zhang, Chengcheng Zhu, Di Wu, Xiaobing Sun, Jianming Yong, Guodong Long:
BADFSS: Backdoor Attacks on Federated Self-Supervised Learning. IJCAI 2024: 548-558 - [c115]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. IJCAI 2024: 3908-3916 - [c114]Chunxu Zhang, Guodong Long, Hongkuan Guo, Xiao Fang, Yang Song, Zhaojie Liu, Guorui Zhou, Zijian Zhang, Yang Liu, Bo Yang:
Federated Adaptation for Foundation Model-based Recommendations. IJCAI 2024: 5453-5461 - [c113]Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
Federated Prompt Learning for Weather Foundation Models on Devices. IJCAI 2024: 5772-5780 - [c112]Guodong Long:
The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence. IJCAI 2024: 8547-8552 - [c111]Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang:
GPFedRec: Graph-Guided Personalization for Federated Recommendation. KDD 2024: 4131-4142 - [c110]Zhenhao Zhang, Yuxi Liu, Jiang Bian, Antonio Jimeno-Yepes, Jun Shen, Fuyi Li, Guodong Long, Flora D. Salim:
Boosting Patient Representation Learning via Graph Contrastive Learning. ECML/PKDD (9) 2024: 335-350 - [c109]Irwin King, Guodong Long, Zenglin Xu, Han Yu:
FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web. WWW (Companion Volume) 2024: 1546-1547 - [c108]Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang:
When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions. WWW 2024: 3632-3642 - [i97]Yiyuan Yang, Guodong Long, Tao Shen, Jing Jiang, Michael Blumenstein:
Dual-Personalizing Adapter for Federated Foundation Models. CoRR abs/2403.19211 (2024) - [i96]Peng Yan, Guodong Long:
Client-supervised Federated Learning: Towards One-model-for-all Personalization. CoRR abs/2403.19499 (2024) - [i95]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. CoRR abs/2404.10942 (2024) - [i94]Chunxu Zhang, Guodong Long, Hongkuan Guo, Xiao Fang, Yang Song, Zhaojie Liu, Guorui Zhou, Zijian Zhang, Yang Liu, Bo Yang:
Federated Adaptation for Foundation Model-based Recommendations. CoRR abs/2405.04840 (2024) - [i93]Shutong Chen, Tianyi Zhou, Guodong Long, Jie Ma, Jing Jiang, Chengqi Zhang:
Multi-Level Additive Modeling for Structured Non-IID Federated Learning. CoRR abs/2405.16472 (2024) - [i92]Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang:
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models. CoRR abs/2405.20348 (2024) - [i91]Zhiwei Li, Guodong Long:
Navigating the Future of Federated Recommendation Systems with Foundation Models. CoRR abs/2406.00004 (2024) - [i90]Peng Yan, Guodong Long, Jing Jiang, Michael Blumenstein:
Personalized Interpretation on Federated Learning: A Virtual Concepts approach. CoRR abs/2406.19631 (2024) - [i89]Zhiwei Li, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach. CoRR abs/2408.08931 (2024) - 2023
- [j33]Yiqiang Chen, Wuliang Huang, Xinlong Jiang, Teng Zhang, Yi Wang, Bingjie Yan, Zhirui Wang, Qian Chen, Yunbing Xing, Dong Li, Guodong Long:
UbiMeta: A Ubiquitous Operating System Model for Metaverse. Int. J. Crowd Sci. 7(4): 180-189 (2023) - [j32]Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Jing Jiang, Guandong Xu:
Attentional Gated Res2Net for Multivariate Time Series Classification. Neural Process. Lett. 55(2): 1371-1395 (2023) - [j31]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Beyond Low-Pass Filtering: Graph Convolutional Networks With Automatic Filtering. IEEE Trans. Knowl. Data Eng. 35(7): 6687-6697 (2023) - [j30]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j29]Guodong Long, Ming Xie, Tao Shen, Tianyi Zhou, Xianzhi Wang, Jing Jiang:
Multi-center federated learning: clients clustering for better personalization. World Wide Web (WWW) 26(1): 481-500 (2023) - [c107]Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang:
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. AAAI 2023: 9953-9961 - [c106]Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Binxing Jiao, Daxin Jiang:
Towards Robust Ranker for Text Retrieval. ACL (Findings) 2023: 5387-5401 - [c105]Xiuying Chen, Guodong Long, Chongyang Tao, Mingzhe Li, Xin Gao, Chengqi Zhang, Xiangliang Zhang:
Improving the Robustness of Summarization Systems with Dual Augmentation. ACL (1) 2023: 6846-6857 - [c104]Weikuan Wang, Tao Shen, Michael Blumenstein, Guodong Long:
Improving Open-Domain Answer Sentence Selection by Distributed Clients with Privacy Preservation. ADMA (5) 2023: 15-29 - [c103]Yang Wang, Xueping Peng, Tao Shen, Allison Clarke, Clement Schlegel, Paul Martin, Guodong Long:
Soft Prompt Transfer for Zero-Shot and Few-Shot Learning in EHR Understanding. ADMA (3) 2023: 18-32 - [c102]Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu:
From Time Series to Multi-modality: Classifying Multivariate Time Series via Both 1D and 2D Representations. ADMA (1) 2023: 19-33 - [c101]Leah Gerrard, Xueping Peng, Allison Clarke, Guodong Long:
Multi-level Transformer for Cancer Outcome Prediction in Large-Scale Claims Data. ADMA (3) 2023: 63-78 - [c100]Wensi Tang, Guodong Long:
WeightRelay: Efficient Heterogeneous Federated Learning on Time Series. AI (1) 2023: 129-140 - [c99]Jianan Yang, Guodong Long:
Concept-Guided Interpretable Federated Learning. AI (2) 2023: 160-172 - [c98]Yucheng Zhou, Guodong Long:
Style-Aware Contrastive Learning for Multi-Style Image Captioning. EACL (Findings) 2023: 2212-2222 - [c97]Yucheng Zhou, Guodong Long:
Multimodal Event Transformer for Image-guided Story Ending Generation. EACL 2023: 3426-3436 - [c96]Yucheng Zhou, Guodong Long:
Improving Cross-modal Alignment for Text-Guided Image Inpainting. EACL 2023: 3437-3448 - [c95]Peng Yan, Guodong Long:
Personalization Disentanglement for Federated Learning. ICME 2023: 318-323 - [c94]Yijun Yang, Tianyi Zhou, Jing Jiang, Guodong Long, Yuhui Shi:
Continual Task Allocation in Meta-Policy Network via Sparse Prompting. ICML 2023: 39623-39638 - [c93]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? ICML 2023: 42280-42303 - [c92]Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang:
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data. IJCAI 2023: 3532-3540 - [c91]Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang:
Dual Personalization on Federated Recommendation. IJCAI 2023: 4558-4566 - [c90]Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Kai Zhang, Daxin Jiang:
UnifieR: A Unified Retriever for Large-Scale Retrieval. KDD 2023: 4787-4799 - [c89]Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Structured Federated Learning through Clustered Additive Modeling. NeurIPS 2023 - [c88]Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu, Guodong Long:
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. NeurIPS 2023 - [c87]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. ECML/PKDD (2) 2023: 52-68 - [i88]Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Chengqi Zhang, Bo Yang:
Dual Personalization on Federated Recommendation. CoRR abs/2301.08143 (2023) - [i87]Zhiwei Li, Guodong Long, Tianyi Zhou:
Federated Recommendation with Additive Personalization. CoRR abs/2301.09109 (2023) - [i86]Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang:
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data. CoRR abs/2301.09152 (2023) - [i85]Yucheng Zhou, Guodong Long:
Multimodal Event Transformer for Image-guided Story Ending Generation. CoRR abs/2301.11357 (2023) - [i84]Yucheng Zhou, Guodong Long:
Improving Cross-modal Alignment for Text-Guided Image Inpainting. CoRR abs/2301.11362 (2023) - [i83]Yucheng Zhou, Guodong Long:
Style-Aware Contrastive Learning for Multi-Style Image Captioning. CoRR abs/2301.11367 (2023) - [i82]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. CoRR abs/2301.11560 (2023) - [i81]Kun Yi, Qi Zhang, Shoujin Wang, Hui He, Guodong Long, Zhendong Niu:
Neural Time Series Analysis with Fourier Transform: A Survey. CoRR abs/2302.02173 (2023) - [i80]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? CoRR abs/2304.04158 (2023) - [i79]Tao Shen, Guodong Long, Xiubo Geng, Chongyang Tao, Tianyi Zhou, Daxin Jiang:
Large Language Models are Strong Zero-Shot Retriever. CoRR abs/2304.14233 (2023) - [i78]Jiazhan Feng, Chongyang Tao, Xiubo Geng, Tao Shen, Can Xu, Guodong Long, Dongyan Zhao, Daxin Jiang:
Knowledge Refinement via Interaction Between Search Engines and Large Language Models. CoRR abs/2305.07402 (2023) - [i77]Chunxu Zhang, Guodong Long, Tianyi Zhou, Peng Yan, Zijian Zhang, Bo Yang:
Graph-guided Personalization for Federated Recommendation. CoRR abs/2305.07866 (2023) - [i76]Chunxu Zhang, Guodong Long, Tianyi Zhou, Xiangyu Zhao, Zijian Zhang, Bo Yang:
IFedRec: Item-Guided Federated Aggregation for Cold-Start. CoRR abs/2305.12650 (2023) - [i75]Shengchao Chen, Guodong Long, Tao Shen, Tianyi Zhou, Jing Jiang:
Spatial-temporal Prompt Learning for Federated Weather Forecasting. CoRR abs/2305.14244 (2023) - [i74]Yijun Yang, Tianyi Zhou, Jing Jiang, Guodong Long, Yuhui Shi:
Continual Task Allocation in Meta-Policy Network via Sparse Prompting. CoRR abs/2305.18444 (2023) - [i73]Xiuying Chen, Guodong Long, Chongyang Tao, Mingzhe Li, Xin Gao, Chengqi Zhang, Xiangliang Zhang:
Improving the Robustness of Summarization Systems with Dual Augmentation. CoRR abs/2306.01090 (2023) - [i72]Peng Yan, Guodong Long:
Personalization Disentanglement for Federated Learning. CoRR abs/2306.03570 (2023) - [i71]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. CoRR abs/2307.01452 (2023) - [i70]Haiyan Zhao, Guodong Long:
One-Shot Pruning for Fast-adapting Pre-trained Models on Devices. CoRR abs/2307.04365 (2023) - [i69]Xiaohan Xu, Chongyang Tao, Tao Shen, Can Xu, Hongbo Xu, Guodong Long, Jianguang Lou:
Re-Reading Improves Reasoning in Language Models. CoRR abs/2309.06275 (2023) - [i68]Shuang Ao, Tianyi Zhou, Guodong Long, Xuan Song, Jing Jiang:
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution. CoRR abs/2309.12529 (2023) - [i67]Yucheng Zhou, Xiubo Geng, Tao Shen, Chongyang Tao, Guodong Long, Jian-Guang Lou, Jianbing Shen:
Thread of Thought Unraveling Chaotic Contexts. CoRR abs/2311.08734 (2023) - [i66]Shengchao Chen, Guodong Long, Jing Jiang, Dikai Liu, Chengqi Zhang:
Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey. CoRR abs/2312.03014 (2023) - 2022
- [j28]Chun Wang, Shirui Pan, Celina Ping Yu, Ruiqi Hu, Guodong Long, Chengqi Zhang:
Deep neighbor-aware embedding for node clustering in attributed graphs. Pattern Recognit. 122: 108230 (2022) - [j27]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. IEEE Trans. Knowl. Data Eng. 34(5): 2293-2305 (2022) - [j26]Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long:
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j25]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Extracting Local Reasoning Chains of Deep Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c86]Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang:
FedProto: Federated Prototype Learning across Heterogeneous Clients. AAAI 2022: 8432-8440 - [c85]Yucheng Zhou, Tao Shen, Xiubo Geng, Guodong Long, Daxin Jiang:
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification. ACL (1) 2022: 2559-2575 - [c84]Jie Ma, Ming Xie, Guodong Long:
Personalized Federated Learning with Robust Clustering Against Model Poisoning. ADMA (2) 2022: 238-252 - [c83]Zhuowei Wang, Guodong Long:
Positive Unlabeled Learning by Sample Selection and Prototype Refinement. ADMA (1) 2022: 304-318 - [c82]Ming Xie, Jie Ma, Guodong Long, Chengqi Zhang:
Robust Clustered Federated Learning with Bootstrap Median-of-Means. APWeb/WAIM (1) 2022: 237-250 - [c81]Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Jing Jiang, Guandong Xu:
Attentional Gated Res2net for Multivariate Time Series Classification. ICASSP 2022: 3308-3312 - [c80]Zhuowei Wang, Jing Jiang, Guodong Long:
Positive Unlabeled Learning by Semi-Supervised Learning. ICIP 2022: 2976-2980 - [c79]Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Michael Blumenstein, Jing Jiang:
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification. ICLR 2022 - [c78]Shuang Ao, Tianyi Zhou, Jing Jiang, Guodong Long, Xuan Song, Chengqi Zhang:
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning. ICML 2022: 822-843 - [c77]Yakun Chen, Zihao Li, Chao Yang, Xianzhi Wang, Guodong Long, Guandong Xu:
Adaptive Graph Recurrent Network for Multivariate Time Series Imputation. ICONIP (5) 2022: 64-73 - [c76]Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang:
Personalized Federated Learning With a Graph. IJCAI 2022: 2575-2582 - [c75]Yang Li, Guodong Long, Tao Shen, Jing Jiang:
Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision. NAACL-HLT (Findings) 2022: 316-326 - [c74]Hao Huang, Xiubo Geng, Guodong Long, Daxin Jiang:
Understand before Answer: Improve Temporal Reading Comprehension via Precise Question Understanding. NAACL-HLT 2022: 375-384 - [c73]Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang:
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. NeurIPS 2022 - [c72]Qi Cheng, Guodong Long:
Federated Learning Operations (FLOps): Challenges, Lifecycle and Approaches. TAAI 2022: 12-17 - [c71]Yucheng Zhou, Xiubo Geng, Tao Shen, Guodong Long, Daxin Jiang:
EventBERT: A Pre-Trained Model for Event Correlation Reasoning. WWW 2022: 850-859 - [e3]Bohan Li, Lin Yue, Jing Jiang, Weitong Chen, Xue Li, Guodong Long, Fei Fang, Han Yu:
Advanced Data Mining and Applications - 17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13087, Springer 2022, ISBN 978-3-030-95404-8 [contents] - [e2]Bohan Li, Lin Yue, Jing Jiang, Weitong Chen, Xue Li, Guodong Long, Fei Fang, Han Yu:
Advanced Data Mining and Applications - 17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13088, Springer 2022, ISBN 978-3-030-95407-9 [contents] - [e1]Guodong Long, Xinghuo Yu, Sen Wang:
AI 2021: Advances in Artificial Intelligence - 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2-4, 2022, Proceedings. Lecture Notes in Computer Science 13151, Springer 2022, ISBN 978-3-030-97545-6 [contents] - [i65]Jie Ma, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
On the Convergence of Clustered Federated Learning. CoRR abs/2202.06187 (2022) - [i64]Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang:
Personalized Federated Learning With Structure. CoRR abs/2203.00829 (2022) - [i63]Yucheng Zhou, Tao Shen, Xiubo Geng, Guodong Long, Daxin Jiang:
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification. CoRR abs/2203.02225 (2022) - [i62]Zhuowei Wang, Tianyi Zhou, Guodong Long, Bo Han, Jing Jiang:
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels. CoRR abs/2205.10110 (2022) - [i61]Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Binxing Jiao, Daxin Jiang:
Towards Robust Ranker for Text Retrieval. CoRR abs/2206.08063 (2022) - [i60]Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang:
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. CoRR abs/2209.10083 (2022) - [i59]Chenglin Wang, Yucheng Zhou, Guodong Long, Xiaodong Wang, Xiaowei Xu:
Unsupervised Knowledge Graph Construction and Event-centric Knowledge Infusion for Scientific NLI. CoRR abs/2210.15248 (2022) - [i58]Yang Li, Canran Xu, Tao Shen, Jing Jiang, Guodong Long:
CCPrompt: Counterfactual Contrastive Prompt-Tuning for Many-Class Classification. CoRR abs/2211.05987 (2022) - [i57]Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang:
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. CoRR abs/2211.13009 (2022) - [i56]Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Guodong Long, Can Xu, Daxin Jiang:
Fine-Grained Distillation for Long Document Retrieval. CoRR abs/2212.10423 (2022) - 2021
- [j24]Zhineng Fu, Weijun Xu, Ruiqi Hu, Guodong Long, Jing Jiang:
MHieR-encoder: Modelling the high-frequency changes across stocks. Knowl. Based Syst. 224: 107092 (2021) - [j23]Xiaohan Zhang, Lu Liu, Guodong Long, Jing Jiang, Shenquan Liu:
Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task. Neural Networks 134: 1-10 (2021) - [j22]Shaoxiong Ji, Shirui Pan, Xue Li, Erik Cambria, Guodong Long, Zi Huang:
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. IEEE Trans. Comput. Soc. Syst. 8(1): 214-226 (2021) - [j21]Lin Yue, Hao Shen, Sen Wang, Robert Boots, Guodong Long, Weitong Chen, Xiaowei Zhao:
Exploring BCI Control in Smart Environments: Intention Recognition Via EEG Representation Enhancement Learning. ACM Trans. Knowl. Discov. Data 15(5): 90:1-90:20 (2021) - [j20]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 32(1): 4-24 (2021) - [c70]Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Guodong Long:
Task Aligned Generative Meta-learning for Zero-shot Learning. AAAI 2021: 8723-8731 - [c69]Hao Huang, Xiubo Geng, Jian Pei, Guodong Long, Daxin Jiang:
Reasoning over Entity-Action-Location Graph for Procedural Text Understanding. ACL/IJCNLP (1) 2021: 5100-5109 - [c68]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Yi Chang:
Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extraction. EMNLP (Findings) 2021: 3002-3012 - [c67]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Sequential Diagnosis Prediction with Transformer and Ontological Representation. ICDM 2021: 489-498 - [c66]Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle:
A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR 2021 - [c65]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang:
Isometric Propagation Network for Generalized Zero-shot Learning. ICLR 2021 - [c64]Yang Zhang, Risa Higashita, Guodong Long, Rong Li, Daisuke Santo, Jiang Liu:
Hierarchical Features Integration and Attention Iteration Network for Juvenile Refractive Power Prediction. ICONIP (2) 2021: 479-490 - [c63]Yang Zhang, Risa Higashita, Yanwu Xu, Daisuke Santo, Yan Hu, Guodong Long, Jiang Liu:
Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network. OMIA@MICCAI 2021: 92-100 - [c62]Shuang Ao, Tianyi Zhou, Guodong Long, Qinghua Lu, Liming Zhu, Jing Jiang:
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum. NeurIPS 2021: 10444-10456 - [c61]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Ying Wang, Yi Chang:
Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion. WWW 2021: 1737-1748 - [i55]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang:
Isometric Propagation Network for Generalized Zero-shot Learning. CoRR abs/2102.02038 (2021) - [i54]Shaoxiong Ji, Teemu Saravirta, Shirui Pan, Guodong Long, Anwar Walid:
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning. CoRR abs/2102.12920 (2021) - [i53]Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Guodong Long:
Task Aligned Generative Meta-learning for Zero-shot Learning. CoRR abs/2103.02185 (2021) - [i52]Xiaohan Zhang, Lu Liu, Guodong Long, Jing Jiang, Shenquan Liu:
Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task. CoRR abs/2103.03679 (2021) - [i51]Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang:
FedProto: Federated Prototype Learning over Heterogeneous Devices. CoRR abs/2105.00243 (2021) - [i50]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering. CoRR abs/2107.04755 (2021) - [i49]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Zhendong Niu, Chengqi Zhang:
MIMO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learning. CoRR abs/2107.09288 (2021) - [i48]Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang:
Federated Learning for Open Banking. CoRR abs/2108.10749 (2021) - [i47]Guodong Long, Tao Shen, Yue Tan, Leah Gerrard, Allison Clarke, Jing Jiang:
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health. CoRR abs/2108.10761 (2021) - [i46]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Yi Chang:
Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extraction. CoRR abs/2109.02403 (2021) - [i45]Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis:
TraverseNet: Unifying Space and Time in Message Passing. CoRR abs/2109.02474 (2021) - [i44]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Sequential Diagnosis Prediction with Transformer and Ontological Representation. CoRR abs/2109.03069 (2021) - [i43]Yang Li, Guodong Long, Tao Shen, Jing Jiang:
Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision. CoRR abs/2109.09036 (2021) - [i42]Yucheng Zhou, Xiubo Geng, Tao Shen, Guodong Long, Daxin Jiang:
EventBERT: A Pre-Trained Model for Event Correlation Reasoning. CoRR abs/2110.06533 (2021) - 2020
- [j19]Cheng Zheng, Qin Zhang, Guodong Long, Chengqi Zhang, Sean D. Young, Wei Wang:
Measuring Time-Sensitive and Topic-Specific Influence in Social Networks With LSTM and Self-Attention. IEEE Access 8: 82481-82492 (2020) - [j18]Yu Zheng, Ruiqi Hu, Sai-Fu Fung, Celina Ping Yu, Guodong Long, Ting Guo, Shirui Pan:
Clustering social audiences in business information networks. Pattern Recognit. 100: 107126 (2020) - [j17]Shirui Pan, Ruiqi Hu, Sai-Fu Fung, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning Graph Embedding With Adversarial Training Methods. IEEE Trans. Cybern. 50(6): 2475-2487 (2020) - [j16]Jing Jiang, Shaoxiong Ji, Guodong Long:
Decentralized Knowledge Acquisition for Mobile Internet Applications. World Wide Web 23(5): 2653-2669 (2020) - [j15]Weitong Chen, Guodong Long, Lina Yao, Quan Z. Sheng:
AMRNN: attended multi-task recurrent neural networks for dynamic illness severity prediction. World Wide Web 23(5): 2753-2770 (2020) - [c60]Ruiqi Hu, Shirui Pan, Guodong Long, Qinghua Lu, Liming Zhu, Jing Jiang:
Going Deep: Graph Convolutional Ladder-Shape Networks. AAAI 2020: 2838-2845 - [c59]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-Shot Learning. AAAI 2020: 4868-4875 - [c58]Yang Li, Guodong Long, Tao Shen, Tianyi Zhou, Lina Yao, Huan Huo, Jing Jiang:
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. AAAI 2020: 8269-8276 - [c57]Weitao Wang, Meng Wang, Sen Wang, Guodong Long, Lina Yao, Guilin Qi, Yang Chen:
One-Shot Learning for Long-Tail Visual Relation Detection. AAAI 2020: 12225-12232 - [c56]Han Zheng, Jing Jiang, Pengfei Wei, Guodong Long, Chengqi Zhang:
Competitive and Cooperative Heterogeneous Deep Reinforcement Learning. AAMAS 2020: 1656-1664 - [c55]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. COLING 2020: 556-567 - [c54]Yang Li, Tao Shen, Guodong Long, Jing Jiang, Tianyi Zhou, Chengqi Zhang:
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. COLING 2020: 1653-1664 - [c53]Tao Shen, Yi Mao, Pengcheng He, Guodong Long, Adam Trischler, Weizhu Chen:
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. EMNLP (1) 2020: 8980-8994 - [c52]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Chengqi Zhang:
BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. ICDM 2020: 412-421 - [c51]Chun Wang, Bo Han, Shirui Pan, Jing Jiang, Gang Niu, Guodong Long:
Cross-Graph: Robust and Unsupervised Embedding for Attributed Graphs with Corrupted Structure. ICDM 2020: 571-580 - [c50]Tao Shen, Xiubo Geng, Guodong Long, Jing Jiang, Chengqi Zhang, Daxin Jiang:
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. IJCAI 2020: 2227-2233 - [c49]Wensi Tang, Lu Liu, Guodong Long:
Interpretable Time-series Classification on Few-shot Samples. IJCNN 2020: 1-8 - [c48]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. KDD 2020: 753-763 - [c47]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. NeurIPS 2020 - [c46]Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long:
Confusable Learning for Large-Class Few-Shot Classification. ECML/PKDD (2) 2020: 707-723 - [c45]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Self-attention Enhanced Patient Journey Understanding in Healthcare System. ECML/PKDD (3) 2020: 719-735 - [p1]Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang:
Federated Learning for Open Banking. Federated Learning 2020: 240-254 - [i41]Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang, Michael Blumenstein:
Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline. CoRR abs/2002.10061 (2020) - [i40]Tao Shen, Yi Mao, Pengcheng He, Guodong Long, Adam Trischler, Weizhu Chen:
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. CoRR abs/2004.14224 (2020) - [i39]Bo Wang, Tao Shen, Guodong Long, Tianyi Zhou, Yi Chang:
Semantic Triple Encoder for Fast Open-Set Link Prediction. CoRR abs/2004.14781 (2020) - [i38]Ming Xie, Guodong Long, Tao Shen, Tianyi Zhou, Xianzhi Wang, Jing Jiang:
Multi-Center Federated Learning. CoRR abs/2005.01026 (2020) - [i37]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. CoRR abs/2005.11650 (2020) - [i36]Wensi Tang, Lu Liu, Guodong Long:
Interpretable Time-series Classification on Few-shot Samples. CoRR abs/2006.02031 (2020) - [i35]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Self-Attention Enhanced Patient Journey Understanding in Healthcare System. CoRR abs/2006.10516 (2020) - [i34]Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle:
A Universal Representation Transformer Layer for Few-Shot Image Classification. CoRR abs/2006.11702 (2020) - [i33]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. CoRR abs/2006.15479 (2020) - [i32]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-shot Learning. CoRR abs/2009.11816 (2020) - [i31]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Chengqi Zhang:
BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. CoRR abs/2009.13252 (2020) - [i30]Yang Li, Tao Shen, Guodong Long, Jing Jiang, Tianyi Zhou, Chengqi Zhang:
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. CoRR abs/2010.03773 (2020) - [i29]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. CoRR abs/2010.04863 (2020) - [i28]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. CoRR abs/2011.00791 (2020) - [i27]Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long:
Confusable Learning for Large-class Few-Shot Classification. CoRR abs/2011.03154 (2020) - [i26]Zhuowei Wang, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long:
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. CoRR abs/2012.00925 (2020)
2010 – 2019
- 2019
- [j14]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Chengqi Zhang:
Salient Subsequence Learning for Time Series Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2193-2207 (2019) - [j13]Xinxin Jiang, Shirui Pan, Guodong Long, Fei Xiong, Jing Jiang, Chengqi Zhang:
Cost-Sensitive Parallel Learning Framework for Insurance Intelligence Operation. IEEE Trans. Ind. Electron. 66(12): 9713-9723 (2019) - [c44]Kaixuan Chen, Lina Yao, Dalin Zhang, Xiaojun Chang, Guodong Long, Sen Wang:
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing. AAAI 2019: 3321-3328 - [c43]Yang Wang, Guodong Long, Xueping Peng, Allison Clarke, Robin Stevenson, Leah Gerrard:
Interactive Deep Metric Learning for Healthcare Cohort Discovery. AusDM 2019: 208-221 - [c42]Shaoxiong Ji, Guodong Long, Shirui Pan, Tianqing Zhu, Jing Jiang, Sen Wang:
Detecting Suicidal Ideation with Data Protection in Online Communities. DASFAA (3) 2019: 225-229 - [c41]Tao Shen, Xiubo Geng, Tao Qin, Daya Guo, Duyu Tang, Nan Duan, Guodong Long, Daxin Jiang:
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base. EMNLP/IJCNLP (1) 2019: 2442-2451 - [c40]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Michael Blumenstein:
Temporal Self-Attention Network for Medical Concept Embedding. ICDM 2019: 498-507 - [c39]Dalin Zhang, Lina Yao, Kaixuan Chen, Guodong Long, Sen Wang:
Collective Protection: Preventing Sensitive Inferences via Integrative Transformation. ICDM 2019: 1498-1503 - [c38]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. IJCAI 2019: 1907-1913 - [c37]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. IJCAI 2019: 3015-3022 - [c36]Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang:
Attributed Graph Clustering: A Deep Attentional Embedding Approach. IJCAI 2019: 3670-3676 - [c35]Fengwen Chen, Shirui Pan, Jing Jiang, Huan Huo, Guodong Long:
DAGCN: Dual Attention Graph Convolutional Networks. IJCNN 2019: 1-8 - [c34]Shaoxiong Ji, Shirui Pan, Guodong Long, Xue Li, Jing Jiang, Zi Huang:
Learning Private Neural Language Modeling with Attentive Aggregation. IJCNN 2019: 1-8 - [c33]Xueping Peng, Guodong Long, Shirui Pan, Jing Jiang, Zhendong Niu:
Attentive Dual Embedding for Understanding Medical Concepts in Electronic Health Records. IJCNN 2019: 1-8 - [c32]Di Wu, Junjun Chen, Nabin Sharma, Shirui Pan, Guodong Long, Michael Blumenstein:
Adversarial Action Data Augmentation for Similar Gesture Action Recognition. IJCNN 2019: 1-8 - [c31]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together. NAACL-HLT (1) 2019: 1256-1266 - [c30]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning to Propagate for Graph Meta-Learning. NeurIPS 2019: 1037-1048 - [i25]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. CoRR abs/1901.00596 (2019) - [i24]Shirui Pan, Ruiqi Hu, Sai-Fu Fung, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning Graph Embedding with Adversarial Training Methods. CoRR abs/1901.01250 (2019) - [i23]Fengwen Chen, Shirui Pan, Jing Jiang, Huan Huo, Guodong Long:
DAGCN: Dual Attention Graph Convolutional Networks. CoRR abs/1904.02278 (2019) - [i22]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. CoRR abs/1905.04042 (2019) - [i21]Shaoxiong Ji, Guodong Long, Shirui Pan, Tianqing Zhu, Jing Jiang, Sen Wang, Xue Li:
Decentralized Learning with Average Difference Aggregation for Proactive Online Social Care. CoRR abs/1905.07665 (2019) - [i20]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. CoRR abs/1906.00121 (2019) - [i19]Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang:
Attributed Graph Clustering: A Deep Attentional Embedding Approach. CoRR abs/1906.06532 (2019) - [i18]Tao Shen, Xiubo Geng, Tao Qin, Guodong Long, Jing Jiang, Daxin Jiang:
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. CoRR abs/1909.02762 (2019) - [i17]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning to Propagate for Graph Meta-Learning. CoRR abs/1909.05024 (2019) - [i16]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Michael Blumenstein:
Temporal Self-Attention Network for Medical Concept Embedding. CoRR abs/1909.06886 (2019) - [i15]Tao Shen, Xiubo Geng, Tao Qin, Daya Guo, Duyu Tang, Nan Duan, Guodong Long, Daxin Jiang:
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base. CoRR abs/1910.05069 (2019) - [i14]Shaoxiong Ji, Shirui Pan, Xue Li, Erik Cambria, Guodong Long, Zi Huang:
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. CoRR abs/1910.12611 (2019) - [i13]Yang Li, Guodong Long, Tao Shen, Tianyi Zhou, Lina Yao, Huan Huo, Jing Jiang:
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. CoRR abs/1911.11899 (2019) - 2018
- [j12]Shaoxiong Ji, Celina Ping Yu, Sai-Fu Fung, Shirui Pan, Guodong Long:
Supervised Learning for Suicidal Ideation Detection in Online User Content. Complex. 2018: 6157249:1-6157249:10 (2018) - [j11]Qinzhe Zhang, Jia Wu, Qin Zhang, Peng Zhang, Guodong Long, Chengqi Zhang:
Dual influence embedded social recommendation. World Wide Web 21(4): 849-874 (2018) - [c29]Forough Rezaei Boroujeni, Sen Wang, Zhihui Li, Nicholas West, Bela Stantic, Lina Yao, Guodong Long:
Trace Ratio Optimization With Feature Correlation Mining for Multiclass Discriminant Analysis. AAAI 2018: 2746-2753 - [c28]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang:
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding. AAAI 2018: 5446-5455 - [c27]Weitong Chen, Sen Wang, Guodong Long, Lina Yao, Quan Z. Sheng, Xue Li:
Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit. ICDM 2018: 917-922 - [c26]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. ICLR (Poster) 2018 - [c25]Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Adversarially Regularized Graph Autoencoder for Graph Embedding. IJCAI 2018: 2609-2615 - [c24]Xiang Zhang, Lina Yao, Chaoran Huang, Sen Wang, Mingkui Tan, Guodong Long, Can Wang:
Multi-modality Sensor Data Classification with Selective Attention. IJCAI 2018: 3111-3117 - [c23]Shuai Zhang, Lina Yao, Aixin Sun, Sen Wang, Guodong Long, Manqing Dong:
NeuRec: On Nonlinear Transformation for Personalized Ranking. IJCAI 2018: 3669-3675 - [c22]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang:
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. IJCAI 2018: 4345-4352 - [c21]Xinxin Jiang, Shirui Pan, Jing Jiang, Guodong Long:
Cross-Domain Deep Learning Approach For Multiple Financial Market Prediction. IJCNN 2018: 1-8 - [c20]Xinxin Jiang, Shirui Pan, Guodong Long, Jiang Chang, Jing Jiang, Chengqi Zhang:
Cost-sensitive Hybrid Neural Networks for Heterogeneous and Imbalanced Data. IJCNN 2018: 1-8 - [i12]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, Chengqi Zhang:
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. CoRR abs/1801.10296 (2018) - [i11]Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang:
Adversarially Regularized Graph Autoencoder. CoRR abs/1802.04407 (2018) - [i10]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. CoRR abs/1804.00857 (2018) - [i9]Xiang Zhang, Lina Yao, Chaoran Huang, Sen Wang, Mingkui Tan, Guodong Long, Can Wang:
Multi-modality Sensor Data Classification with Selective Attention. CoRR abs/1804.05493 (2018) - [i8]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Fast Directional Self-Attention Mechanism. CoRR abs/1805.00912 (2018) - [i7]Shuai Zhang, Lina Yao, Aixin Sun, Sen Wang, Guodong Long, Manqing Dong:
NeuRec: On Nonlinear Transformation for Personalized Ranking. CoRR abs/1805.03002 (2018) - [i6]Kaixuan Chen, Lina Yao, Dalin Zhang, Xiaojun Chang, Guodong Long, Sen Wang:
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing. CoRR abs/1811.05299 (2018) - [i5]Ruiqi Hu, Celina Ping Yu, Sai-Fu Fung, Shirui Pan, Haishuai Wang, Guodong Long:
Universal Network Representation for Heterogeneous Information Networks. CoRR abs/1811.12157 (2018) - [i4]Shaoxiong Ji, Shirui Pan, Guodong Long, Xue Li, Jing Jiang, Zi Huang:
Learning Private Neural Language Modeling with Attentive Aggregation. CoRR abs/1812.07108 (2018) - 2017
- [j10]Qinzhe Zhang, Jia Wu, Peng Zhang, Guodong Long, Chengqi Zhang:
Collective Hyping Detection System for Identifying Online Spam Activities. IEEE Intell. Syst. 32(5): 53-63 (2017) - [j9]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Boosting for graph classification with universum. Knowl. Inf. Syst. 50(1): 53-77 (2017) - [j8]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Task Sensitive Feature Exploration and Learning for Multitask Graph Classification. IEEE Trans. Cybern. 47(3): 744-758 (2017) - [j7]Sen Wang, Xue Li, Xiaojun Chang, Lina Yao, Quan Z. Sheng, Guodong Long:
Learning Multiple Diagnosis Codes for ICU Patients with Local Disease Correlation Mining. ACM Trans. Knowl. Discov. Data 11(3): 31:1-31:21 (2017) - [c19]Chun Wang, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang:
MGAE: Marginalized Graph Autoencoder for Graph Clustering. CIKM 2017: 889-898 - [c18]Ruiqi Hu, Shirui Pan, Jing Jiang, Guodong Long:
Graph Ladder Networks for Network Classification. CIKM 2017: 2103-2106 - [c17]Ruiqi Hu, Celina Ping Yu, Sai-Fu Fung, Shirui Pan, Haishuai Wang, Guodong Long:
Universal network representation for heterogeneous information networks. IJCNN 2017: 388-395 - [i3]Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, Chengqi Zhang:
DiSAN: Directional Self-Attention Network for RNN/CNN-free Language Understanding. CoRR abs/1709.04696 (2017) - [i2]Meng Wang, Mengyue Liu, Jun Liu, Sen Wang, Guodong Long, Buyue Qian:
Safe Medicine Recommendation via Medical Knowledge Graph Embedding. CoRR abs/1710.05980 (2017) - 2016
- [j6]Xingzhong Du, Yan Yan, Pingbo Pan, Guodong Long, Lei Zhao:
Multiple graph unsupervised feature selection. Signal Process. 120: 754-760 (2016) - [j5]Qin Zhang, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang, Xindong Wu:
Online Learning from Trapezoidal Data Streams. IEEE Trans. Knowl. Data Eng. 28(10): 2709-2723 (2016) - [j4]Sen Wang, Xiaojun Chang, Xue Li, Guodong Long, Lina Yao, Quan Z. Sheng:
Diagnosis Code Assignment Using Sparsity-Based Disease Correlation Embedding. IEEE Trans. Knowl. Data Eng. 28(12): 3191-3202 (2016) - [j3]Peng Zhang, Jing He, Guodong Long, Guangyan Huang, Chengqi Zhang:
Towards Anomalous Diffusion Sources Detection in a Large Network. ACM Trans. Internet Techn. 16(1): 2:1-2:24 (2016) - [j2]Sen Wang, Pingbo Pan, Guodong Long, Weitong Chen, Xue Li, Quan Z. Sheng:
Compact representation for large-scale unconstrained video analysis. World Wide Web 19(2): 231-246 (2016) - [c16]Yan Yan, Zhongwen Xu, Ivor W. Tsang, Guodong Long, Yi Yang:
Robust Semi-Supervised Learning through Label Aggregation. AAAI 2016: 2244-2250 - [c15]Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann:
Dynamic Concept Composition for Zero-Example Event Detection. AAAI 2016: 3464-3470 - [c14]Qinzhe Zhang, Jia Wu, Hong Yang, Weixue Lu, Guodong Long, Chengqi Zhang:
Global and Local Influence-based Social Recommendation. CIKM 2016: 1917-1920 - [c13]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, Chengqi Zhang:
Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. ICDM 2016: 669-678 - [c12]Ruiqi Hu, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang, Chengqi Zhang:
Co-clustering enterprise social networks. IJCNN 2016: 107-114 - [c11]Yu Bai, Haishuai Wang, Jia Wu, Yun Zhang, Jing Jiang, Guodong Long:
Evolutionary lazy learning for Naive Bayes classification. IJCNN 2016: 3124-3129 - [c10]Qinzhe Zhang, Qin Zhang, Guodong Long, Peng Zhang, Chengqi Zhang:
Exploring Heterogeneous Product Networks for Discovering Collective Marketing Hyping Behavior. PAKDD (1) 2016: 40-51 - [i1]Xiaojun Chang, Yi Yang, Guodong Long, Chengqi Zhang, Alexander G. Hauptmann:
Dynamic Concept Composition for Zero-Example Event Detection. CoRR abs/1601.03679 (2016) - 2015
- [j1]Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, Chengqi Zhang:
Finding the best not the most: regularized loss minimization subgraph selection for graph classification. Pattern Recognit. 48(11): 3783-3796 (2015) - [c9]Xinxin Jiang, Wei Liu, Longbing Cao, Guodong Long:
Coupled Collaborative Filtering for Context-aware Recommendation. AAAI 2015: 4172-4173 - [c8]Qinzhe Zhang, Litao Yu, Guodong Long:
SocialTrail: Recommending Social Trajectories from Location-Based Social Networks. ADC 2015: 314-317 - [c7]Sayan Unankard, Xue Li, Guodong Long:
Invariant Event Tracking on Social Networks. DASFAA (2) 2015: 517-521 - [c6]Qin Zhang, Peng Zhang, Guodong Long, Wei Ding, Chengqi Zhang, Xindong Wu:
Towards Mining Trapezoidal Data Streams. ICDM 2015: 1111-1116 - [c5]Xinxin Jiang, Xueping Peng, Guodong Long:
Discovering Sequential Rental Patterns by Fleet Tracking. ICDS 2015: 42-49 - 2014
- [b1]Guodong Long:
Instance-based and feature-based classification enhancement for short & sparse texts. University of Technology Sydney, Australia, 2014 - 2013
- [c4]Guodong Long, Jing Jiang:
Graph Based Feature Augmentation for Short and Sparse Text Classification. ADMA (1) 2013: 456-467 - [c3]Jing Jiang, Jie Lu, Guangquan Zhang, Guodong Long:
Optimal Cloud Resource Auto-Scaling for Web Applications. CCGRID 2013: 58-65 - 2012
- [c2]Guodong Long, Ling Chen, Xingquan Zhu, Chengqi Zhang:
TCSST: transfer classification of short & sparse text using external data. CIKM 2012: 764-772 - 2011
- [c1]Jing Jiang, Jie Lu, Guangquan Zhang, Guodong Long:
Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop. SERVICES 2011: 490-497
Coauthor Index
[c119] [c115] [c113] [i97] [i95] [i93] [i92] [i90] [i89] [j32] [j31] [j30] [j29] [c107] [c94] [c93] [c92] [c89] [c87] [i86] [i82] [i80] [i75] [i74] [i71] [i68] [i66] [j27] [j26] [j25] [c86] [c81] [c80] [c79] [c78] [c76] [c75] [c73] [e3] [e2] [i65] [i64] [i62] [i60] [i58] [i57] [j24] [j23] [c67] [c66] [c65] [c62] [i55] [i52] [i51] [i50] [i48] [i47] [i44] [i43] [j17] [j16] [c60] [c59] [c58] [c56] [c55] [c54] [c52] [c51] [c50] [c48] [c47] [c46] [c45] [p1] [i41] [i38] [i37] [i35] [i34] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [j13] [c42] [c40] [c38] [c37] [c36] [c35] [c34] [c33] [c31] [c30] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i13] [c28] [c26] [c25] [c22] [c21] [c20] [i12] [i11] [i10] [i8] [i4] [c19] [c18] [i3] [c12] [c11] [c4] [c3] [c1]
[c123] [c122] [c121] [c120] [c119] [c113] [i97] [j29] [c106] [c104] [c103] [c92] [c90] [i86] [i79] [i78] [i75] [i69] [i67] [c85] [c75] [c71] [i63] [i61] [i58] [i56] [c68] [c67] [c61] [i49] [i47] [i46] [i44] [i43] [i42] [c58] [c55] [c54] [c53] [c52] [c50] [c45] [i40] [i39] [i38] [i35] [i31] [i30] [i29] [c41] [c40] [c31] [i18] [i16] [i15] [i13] [c28] [c26] [c22] [i12] [i10] [i8] [i3]
[c115] [c113] [i95] [i93] [i92] [i89] [j31] [j30] [c107] [c105] [c93] [c91] [c89] [c87] [i88] [i82] [i80] [i73] [i71] [i66] [j28] [j27] [j25] [c86] [c82] [c78] [i65] [i57] [j20] [c65] [i55] [i50] [i49] [i48] [j19] [j17] [c59] [c56] [c55] [c54] [c52] [c50] [c48] [c47] [p1] [i37] [i33] [i32] [i31] [i30] [i29] [i28] [j14] [j13] [c38] [c37] [c36] [c31] [c30] [i25] [i24] [i22] [i20] [i19] [i17] [j11] [c28] [c26] [c25] [c22] [c20] [i12] [i11] [i10] [i8] [j10] [j9] [j8] [i3] [j5] [j3] [c15] [c14] [c13] [c12] [c10] [i1] [j1] [c6] [c2]
[c121] [c118] [c111] [c108] [i93] [i89] [j29] [c94] [c93] [c91] [c89] [c87] [i88] [i87] [i82] [i80] [i79] [i77] [i76] [i75] [i74] [i68] [j27] [j25] [c86] [c79] [c78] [c76] [c73] [i65] [i64] [i62] [i60] [c68] [c65] [c62] [c61] [i55] [i51] [i46] [c59] [c58] [c54] [i41] [i39] [i38] [i33] [i32] [i30] [c37] [c31] [c30] [i22] [i17] [i13] [c28] [c26] [c22] [i12] [i10] [i8] [i3]
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last updated on 2024-11-06 20:27 CET by the dblp team
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