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ORCIDJing Jiang 0002
Person information
- affiliation: University of Technology Sydney, Australia
Other persons with the same name
- Jing Jiang — disambiguation page
- Jing Jiang 0001
![[0000-0002-3035-0074]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-3035-0074")
— Singapore Management University, School of Information Systems, Singapore (and 1 more) - Jing Jiang 0003 — Guangxi Normal University, Guilin, China
- Jing Jiang 0004 — Northumbria University, UK (and 2 more)
- Jing Jiang 0005 — Beihang University, State Key Laboratory of Software Development Environment, Beijing, China (and 1 more)
- Jing Jiang 0006 — Texas Instruments Inc., USA (and 1 more)
- Jing Jiang 0007 — University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Jing Jiang 0008 — China Agricultural University, Beijing, China
- Jing Jiang 0009 — Hangzhou Dianzi University, Hangzhou, China
- Jing Jiang 0010 — Texas A&M University, College Station, TX, USA
- Jing Jiang 0011 — Auckland University of Technology, New Zealand
- Jing Jiang 0012 — Qualcomm Technologies, Inc., Beijing, China
- Jing Jiang 0014 — Wayne State University, Detroit, MI, USA
- Jing Jiang 0015 — Air Force Early Warning Academy, Wuhan, Hubei, China
- Jing Jiang 0016 — Qilu Normal University, Jinan, China
- Jing Jiang 0017 — China University of Mining Technology, Beijing, China (and 1 more)
- Jing Jiang 0019 — Nanjing University of Posts and Telecommunications, China
- Jing Jiang 0020 — NPC Beijing Richfit Information Technology Co., Ltd., Beijing, China
- Jing Jiang 0021 — Jiangsu University, Zhenjiang, China (and 1 more)
- Jing Jiang 0022 — Chongqing University of Arts and Sciences, China
- Jing Jiang 0023 — Shanghai Jiao Tong University, Shanghai, China
- Jing Jiang 0024 — Wuhan University of Technology, Wuhan, Hubei, China
- Jing Jiang 0025 — Bank of Communications, Shanghai, China
- Jing Jiang 0026 — Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China
- Jin Jiang 0001 (aka: Jing Jiang 0027) — University of Western Ontario, Department of Electrical and Computer Engineering, London, ON, Canada (and 1 more)
- Jing Jiang 0028 — Northeastern University, Shenyang, China
- Jing Jiang 0029 — Stanford University, CA, USA
- Jing Jiang 0030 — State Power Economic Research Institute of State Grid Corporation of China, Beijing, China
- Jing Jiang 0031 — LifeFoundry Inc., Champaign, IL, USA (and 1 more)
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2020 – today
- 2024
[j13]Zhihong Deng, Zuyue Fu, Lingxiao Wang, Zhuoran Yang, Chenjia Bai, Tianyi Zhou, Zhaoran Wang, Jing Jiang:
False Correlation Reduction for Offline Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(2): 1199-1211 (2024)- [c68]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 - [i63]Yiyuan Yang, Guodong Long, Tao Shen, Jing Jiang, Michael Blumenstein:
Dual-Personalizing Adapter for Federated Foundation Models. CoRR abs/2403.19211 (2024) - [i62]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. CoRR abs/2404.10942 (2024) - [i61]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) - [i60]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) - [i59]Peng Yan, Guodong Long, Jing Jiang, Michael Blumenstein:
Personalized Interpretation on Federated Learning: A Virtual Concepts approach. CoRR abs/2406.19631 (2024) - 2023
- [j12]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) - [j11]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) - [j10]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j9]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) - [c67]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 - [c66]Han Zheng, Xufang Luo, Pengfei Wei, Xuan Song, Dongsheng Li, Jing Jiang:
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning. AAAI 2023: 11372-11380 - [c65]Yijun Yang, Tianyi Zhou, Jing Jiang, Guodong Long, Yuhui Shi:
Continual Task Allocation in Meta-Policy Network via Sparse Prompting. ICML 2023: 39623-39638 - [c64]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? ICML 2023: 42280-42303 - [c63]Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang:
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data. IJCAI 2023: 3532-3540 - [c62]Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Structured Federated Learning through Clustered Additive Modeling. NeurIPS 2023 - [c61]Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, Zhiqiang Xu, Jing Jiang, Xiang Yin:
Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective. NeurIPS 2023 - [c60]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 - [i58]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) - [i57]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) - [i56]Han Zheng, Xufang Luo, Pengfei Wei, Xuan Song, Dongsheng Li, Jing Jiang:
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning. CoRR abs/2303.07693 (2023) - [i55]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Does Continual Learning Equally Forget All Parameters? CoRR abs/2304.04158 (2023) - [i54]Shengchao Chen, Guodong Long, Tao Shen, Tianyi Zhou, Jing Jiang:
Spatial-temporal Prompt Learning for Federated Weather Forecasting. CoRR abs/2305.14244 (2023) - [i53]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) - [i52]Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang:
Causal Reinforcement Learning: A Survey. CoRR abs/2307.01452 (2023) - [i51]Shuang Ao, Tianyi Zhou, Guodong Long, Xuan Song, Jing Jiang:
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution. CoRR abs/2309.12529 (2023) - [i50]Yijun Yang, Tianyi Zhou, Kanxue Li, Dapeng Tao, Lusong Li, Li Shen, Xiaodong He, Jing Jiang, Yuhui Shi:
Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld. CoRR abs/2311.16714 (2023) - [i49]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
- [j8]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) - [j7]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) - [j6]Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Extracting Local Reasoning Chains of Deep Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c59]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 - [c58]Chao Yang, Xianzhi Wang, Lina Yao, Jing Jiang, Guandong Xu:
An Explanation Module for Deep Neural Networks Facing Multivariate Time Series Classification. AI 2022: 3-14 - [c57]Yang Wang, Xueping Peng, Allison Clarke, Clement Schlegel, Jing Jiang:
Machine Teaching-Based Efficient Labelling for Cross-unit Healthcare Data Modelling. AI 2022: 320-331 - [c56]Leah Gerrard, Xueping Peng, Allison Clarke, Clement Schlegel, Jing Jiang:
Predicting Outcomes for Cancer Patients with Transformer-Based Multi-task Learning. AI 2022: 381-392 - [c55]Yijun Yang, Jing Jiang, Zhuowei Wang, Qiqi Duan, Yuhui Shi:
BiES: Adaptive Policy Optimization for Model-Based Offline Reinforcement Learning. AI 2022: 570-581 - [c54]Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Jing Jiang, Guandong Xu:
Attentional Gated Res2net for Multivariate Time Series Classification. ICASSP 2022: 3308-3312 - [c53]Zhuowei Wang, Jing Jiang, Guodong Long:
Positive Unlabeled Learning by Semi-Supervised Learning. ICIP 2022: 2976-2980 - [c52]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 - [c51]Yijun Yang, Jing Jiang, Tianyi Zhou, Jie Ma, Yuhui Shi:
Pareto Policy Pool for Model-based Offline Reinforcement Learning. ICLR 2022 - [c50]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 - [c49]Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang:
Personalized Federated Learning With a Graph. IJCAI 2022: 2575-2582 - [c48]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 - [c47]Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang:
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. NeurIPS 2022 - [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 I. Lecture Notes in Computer Science 13087, Springer 2022, ISBN 978-3-030-95404-8 [contents] - [e1]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] - [i48]Jie Ma, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang:
On the Convergence of Clustered Federated Learning. CoRR abs/2202.06187 (2022) - [i47]Fengwen Chen, Guodong Long, Zonghan Wu, Tianyi Zhou, Jing Jiang:
Personalized Federated Learning With Structure. CoRR abs/2203.00829 (2022) - [i46]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) - [i45]Pengfei Wei, Lingdong Kong, Xinghua Qu, Xiang Yin, Zhiqiang Xu, Jing Jiang, Zejun Ma:
Unsupervised Video Domain Adaptation: A Disentanglement Perspective. CoRR abs/2208.07365 (2022) - [i44]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) - [i43]Yang Li, Canran Xu, Tao Shen, Jing Jiang, Guodong Long:
CCPrompt: Counterfactual Contrastive Prompt-Tuning for Many-Class Classification. CoRR abs/2211.05987 (2022) - [i42]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) - 2021
- [j5]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) - [j4]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) - [c46]Lin Yue, Dongyuan Tian, Jing Jiang, Lina Yao, Weitong Chen, Xiaowei Zhao:
Intention Recognition from Spatio-Temporal Representation of EEG Signals. ADC 2021: 1-12 - [c45]Ming Xie, Jing Jiang, Tao Shen, Yang Wang, Leah Gerrard, Allison Clarke:
A Green Pipeline for Out-of-Domain Public Sentiment Analysis. ADMA 2021: 190-202 - [c44]Chang Shao, Qi Zhao, Yuhui Shi, Jing Jiang:
Generalized Test Suite for Continuous Dynamic Multi-objective Optimization. EMO 2021: 205-217 - [c43]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Sequential Diagnosis Prediction with Transformer and Ontological Representation. ICDM 2021: 489-498 - [c42]Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle:
A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR 2021 - [c41]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang:
Isometric Propagation Network for Generalized Zero-shot Learning. ICLR 2021 - [c40]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 - [i41]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) - [i40]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) - [i39]Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang:
FedProto: Federated Prototype Learning over Heterogeneous Devices. CoRR abs/2105.00243 (2021) - [i38]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) - [i37]Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang:
Federated Learning for Open Banking. CoRR abs/2108.10749 (2021) - [i36]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) - [i35]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Sequential Diagnosis Prediction with Transformer and Ontological Representation. CoRR abs/2109.03069 (2021) - [i34]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) - [i33]Zhihong Deng, Zuyue Fu, Lingxiao Wang, Zhuoran Yang, Chenjia Bai, Zhaoran Wang, Jing Jiang:
SCORE: Spurious COrrelation REduction for Offline Reinforcement Learning. CoRR abs/2110.12468 (2021) - [i32]Zhining Liu, Zhepei Wei, Erxin Yu, Qiang Huang, Kai Guo, Boyang Yu, Zhaonian Cai, Hangting Ye, Wei Cao, Jiang Bian, Pengfei Wei, Jing Jiang, Yi Chang:
IMBENS: Ensemble Class-imbalanced Learning in Python. CoRR abs/2111.12776 (2021) - [i31]Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning. CoRR abs/2111.12791 (2021) - 2020
- [j3]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) - [j2]Jing Jiang, Shaoxiong Ji, Guodong Long:
Decentralized Knowledge Acquisition for Mobile Internet Applications. World Wide Web 23(5): 2653-2669 (2020) - [c39]Ruiqi Hu, Shirui Pan, Guodong Long, Qinghua Lu, Liming Zhu, Jing Jiang:
Going Deep: Graph Convolutional Ladder-Shape Networks. AAAI 2020: 2838-2845 - [c38]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-Shot Learning. AAAI 2020: 4868-4875 - [c37]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 - [c36]Han Zheng, Jing Jiang, Pengfei Wei, Guodong Long, Chengqi Zhang:
Competitive and Cooperative Heterogeneous Deep Reinforcement Learning. AAMAS 2020: 1656-1664 - [c35]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. COLING 2020: 556-567 - [c34]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 - [c33]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 - [c32]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 - [c31]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 - [c30]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 - [c29]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. NeurIPS 2020 - [c28]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. NeurIPS 2020 - [c27]Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long:
Confusable Learning for Large-Class Few-Shot Classification. ECML/PKDD (2) 2020: 707-723 - [c26]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 - [i30]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) - [i29]Ming Xie, Guodong Long, Tao Shen, Tianyi Zhou, Xianzhi Wang, Jing Jiang:
Multi-Center Federated Learning. CoRR abs/2005.01026 (2020) - [i28]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) - [i27]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang:
Self-Attention Enhanced Patient Journey Understanding in Healthcare System. CoRR abs/2006.10516 (2020) - [i26]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) - [i25]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) - [i24]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Attribute Propagation Network for Graph Zero-shot Learning. CoRR abs/2009.11816 (2020) - [i23]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) - [i22]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) - [i21]Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang:
RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. CoRR abs/2010.04863 (2020) - [i20]Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang:
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler. CoRR abs/2010.08830 (2020) - [i19]Han Zheng, Pengfei Wei, Jing Jiang, Guodong Long, Qinghua Lu, Chengqi Zhang:
Cooperative Heterogeneous Deep Reinforcement Learning. CoRR abs/2011.00791 (2020) - [i18]Bingcong Li, Bo Han, Zhuowei Wang, Jing Jiang, Guodong Long:
Confusable Learning for Large-class Few-Shot Classification. CoRR abs/2011.03154 (2020) - [i17]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
- [j1]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) - [c25]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 - [c24]Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Michael Blumenstein:
Temporal Self-Attention Network for Medical Concept Embedding. ICDM 2019: 498-507 - [c23]Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang:
Graph WaveNet for Deep Spatial-Temporal Graph Modeling. IJCAI 2019: 1907-1913 - [c22]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 - [c21]Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang:
Attributed Graph Clustering: A Deep Attentional Embedding Approach. IJCAI 2019: 3670-3676 - [c20]Fengwen Chen, Shirui Pan, Jing Jiang, Huan Huo, Guodong Long:
DAGCN: Dual Attention Graph Convolutional Networks. IJCNN 2019: 1-8 - [c19]Shaoxiong Ji, Shirui Pan, Guodong Long, Xue Li, Jing Jiang, Zi Huang:
Learning Private Neural Language Modeling with Attentive Aggregation. IJCNN 2019: 1-8 - [c18]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 - [c17]Di Wu, Ruiqi Hu, Yu Zheng, Jing Jiang, Nabin Sharma, Michael Blumenstein:
Feature-Dependent Graph Convolutional Autoencoders with Adversarial Training Methods. IJCNN 2019: 1-8 - [c16]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 - [c15]Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang:
Learning to Propagate for Graph Meta-Learning. NeurIPS 2019: 1037-1048 - [i16]