Dongjin Song

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 79

Top Topics

Multivariate Time Series

Abnormal Behavior

Graph Representation

Top Venues

Publications

Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan
Online GNN Evaluation Under Test-time Graph Distribution Shifts. CoRR (2024)
Jiangwei Wang, Lili Su, Songyang Han, Dongjin Song, Fei Miao
Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing. ACM Trans. Cyber Phys. Syst. 8 (2) (2024)
Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao
Topology-aware Embedding Memory for Learning on Expanding Graphs. CoRR (2024)
Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. KDD (2024)
Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao
Topology-aware Embedding Memory for Continual Learning on Expanding Networks. KDD (2024)
Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song
Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference. CoRR (2024)
Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song
International Trade Flow Prediction with Bilateral Trade Provisions. CoRR (2024)
Soumyashree Sahoo, Chinmaey Shende, Md Zakir Hossain, Parit Patel, Xinyu Wang, Md Ishtyaq Mahmud, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang
Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement. CHASE (2024)
Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting. CoRR (2024)
Qianying Ren, Dongsheng Luo, Dongjin Song
Rank Supervised Contrastive Learning for Time Series Classification. CoRR (2024)
Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding
Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements. CoRR (2024)
Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen
Foundation Models for Time Series Analysis: A Tutorial and Survey. KDD (2024)
Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
Empowering Time Series Analysis with Large Language Models: A Survey. CoRR (2024)
Xikun Zhang, Dongjin Song, Dacheng Tao
Continual Learning on Graphs: Challenges, Solutions, and Opportunities. CoRR (2024)
Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan
Online GNN Evaluation Under Test-time Graph Distribution Shifts. ICLR (2024)
Zijie Pan, Yushan Jiang, Dongjin Song, Sahil Garg, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka
Structural Knowledge Informed Continual Multivariate Time Series Forecasting. CoRR (2024)
Xikun Zhang, Dongjin Song, Yushan Jiang, Yixin Chen, Dacheng Tao
Learning System Dynamics without Forgetting. CoRR (2024)
Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen
Foundation Models for Time Series Analysis: A Tutorial and Survey. CoRR (2024)
Lisha Ye, Jianfeng Zhou, Zhe Yin, Kunpeng Han, Haoyuan Hu, Dongjin Song
A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System. SDM (2024)
Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu
Tutorials at The Web Conference 2023. WWW (Companion Volume) (2023)
Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka
The 9th SIGKDD International Workshop on Mining and Learning from Time Series. KDD (2023)
Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su
Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles. IROS (2023)
Chinmaey Shende, Soumyashree Sahoo, Stephen Sam, Parit Patel, Reynaldo Morillo, Xinyu Wang, Shweta Ware, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang
Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7 (3) (2023)
Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian
Asynchronous Distributed Bilevel Optimization. ICLR (2023)
Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. CoRR (2023)
Chang Li, Dongjin Song, Dacheng Tao
HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings. ICLR (2023)
Yang Jiao, Kai Yang, Dongjin Song
Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis. CoRR (2023)
Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su
Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles. CoRR (2023)
Jiangwei Wang, Lili Su, Songyang Han, Dongjin Song, Fei Miao
Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing. CoRR (2023)
Yushan Jiang, Wenchao Yu, Dongjin Song, Lu Wang, Wei Cheng, Haifeng Chen
FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation. KDD (2023)
Xikun Zhang, Dongjin Song, Dacheng Tao
Hierarchical Prototype Networks for Continual Graph Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45 (4) (2023)
Yushan Jiang, Wenchao Yu, Dongjin Song, Wei Cheng, Haifeng Chen
Interpretable Skill Learning for Dynamic Treatment Regimes through Imitation. CISS (2023)
Xikun Zhang, Dongjin Song, Dacheng Tao
CGLB: Benchmark Tasks for Continual Graph Learning. NeurIPS (2022)
Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. KDD (2022)
Yang Jiao, Kai Yang, Dongjin Song, Dacheng Tao
TimeAutoAD: Autonomous Anomaly Detection With Self-Supervised Contrastive Loss for Multivariate Time Series. IEEE Trans. Netw. Sci. Eng. 9 (3) (2022)
Yang Jiao, Kai Yang, Dongjin Song
Distributed Distributionally Robust Optimization with Non-Convex Objectives. NeurIPS (2022)
Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng, Bo Zong, Takehiko Mizoguchi, Cristian Lumezanu, Haifeng Chen, Jiebo Luo
Deep Federated Anomaly Detection for Multivariate Time Series Data. Big Data (2022)
Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian
Asynchronous Distributed Bilevel Optimization. CoRR (2022)
Xikun Zhang, Dongjin Song, Dacheng Tao
Sparsified Subgraph Memory for Continual Graph Representation Learning. ICDM (2022)
Yang Jiao, Kai Yang, Dongjin Song
Distributed Distributionally Robust Optimization with Non-Convex Objectives. CoRR (2022)
Jurijs Nazarovs, Cristian Lumezanu, Qianying Ren, Yuncong Chen, Takehiko Mizoguchi, Dongjin Song, Haifeng Chen
Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series. CoRR (2022)
Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng, Bo Zong, Takehiko Mizoguchi, Cristian Lumezanu, Haifeng Chen, Jiebo Luo
Deep Federated Anomaly Detection for Multivariate Time Series Data. CoRR (2022)
Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection. ACM Multimedia (2021)
Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen
Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization. CIKM (2021)
Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, Yevgeniy Vorobeychik
FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems. CVPR (2021)
Xikun Zhang, Dongjin Song, Dacheng Tao
Hierarchical Prototype Networks for Continual Graph Representation Learning. CoRR (2021)
Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang
Multi-Task Recurrent Modular Networks. AAAI (2021)
Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection. CoRR (2021)
Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. AAAI (2021)
Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang
Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection. SDM (2021)
Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang
Unsupervised Document Embedding via Contrastive Augmentation. CoRR (2021)
Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, Yevgeniy Vorobeychik
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems. CoRR (2021)
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) (2021)
Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series. CoRR (2021)
Yang Jiao, Kai Yang, Shaoyu Dou, Pan Luo, Sijia Liu, Dongjin Song
TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series. CoRR (2020)
Bo Dong, Cristian Lumezanu, Yuncong Chen, Dongjin Song, Takehiko Mizoguchi, Haifeng Chen, Latifur Khan
At the Speed of Sound: Efficient Audio Scene Classification. ICMR (2020)
Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation. CoRR (2020)
Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation. AAAI (2020)
Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang
Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. AAAI (2020)
Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen
Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval. AAAI (2020)
Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
Robust Graph Representation Learning via Neural Sparsification. ICML (2020)
Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjin Song, Haifeng Chen, Yun Fu
Inductive and Unsupervised Representation Learning on Graph Structured Objects. ICLR (2020)
Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
Node Classification in Temporal Graphs Through Stochastic Sparsification and Temporal Structural Convolution. ECML/PKDD (3) (2020)
Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla
Heterogeneous Graph Neural Network. KDD (2019)
Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang
Deep Co-Clustering. SDM (2019)
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)
Chang Li, Dongjin Song, Dacheng Tao
Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification. KDD (2019)
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 (2018)
Wenchao Yu, Cheng Zheng, Wei Cheng, Charu C. Aggarwal, Dongjin Song, Bo Zong, Haifeng Chen, Wei Wang
Learning Deep Network Representations with Adversarially Regularized Autoencoders. KDD (2018)
Dongjin Song, Ning Xia, Wei Cheng, Haifeng Chen, Dacheng Tao
Deep r -th Root of Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval. KDD (2018)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
Exemplar-centered Supervised Shallow Parametric Data Embedding. IJCAI (2017)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
Exemplar-Centered Supervised Shallow Parametric Data Embedding. CoRR (2017)
Ding Li, Dongjin Song
Detecting Low Rating Android Apps Before They Have Reached the Market. CoRR (2017)
Tingyang Xu, Tan Yan, Dongjin Song, Wei Cheng, Haifeng Chen, Geoff Jiang, Jinbo Bi
Identifying and quantifying nonlinear structured relationships in complex manufactural systems. IEEE BigData (2017)
Jingchao Ni, Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, Xiang Zhang
Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems. ICDM (2017)
Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. IJCAI (2017)
Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction. CoRR (2017)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
A Shallow High-Order Parametric Approach to Data Visualization and Compression. CoRR (2016)
Dongjin Song, Wei Liu, David A. Meyer
Fast Structural Binary Coding. IJCAI (2016)
Dongjin Song, David A. Meyer
Recommending Positive Links in Signed Social Networks by Optimizing a Generalized AUC. AAAI (2015)
Dongjin Song, Wei Liu, Tianyi Zhou, Dacheng Tao, David A. Meyer
Efficient Robust Conditional Random Fields. IEEE Trans. Image Process. 24 (10) (2015)
Dongjin Song, David A. Meyer, Dacheng Tao
Efficient Latent Link Recommendation in Signed Networks. KDD (2015)
Dongjin Song, David A. Meyer, Dacheng Tao
Top-k Link Recommendation in Social Networks. ICDM (2015)
Dongjin Song, Wei Liu, David A. Meyer, Dacheng Tao, Rongrong Ji
Rank Preserving Hashing for Rapid Image Search. DCC (2015)
Dongjin Song, Wei Liu, Rongrong Ji, David A. Meyer, John R. Smith
Top Rank Supervised Binary Coding for Visual Search. ICCV (2015)
Dongjin Song, David A. Meyer
Link sign prediction and ranking in signed directed social networks. Soc. Netw. Anal. Min. 5 (1) (2015)
Dongjin Song, Susu Nousala, Yongqi Lou
Design Process as Communication Agency for Value Co-Creation in Open Social Innovation Project: - A Case Study of QuYang Community in Shanghai. HCI (12) (2015)
Rex W. Douglass, David A. Meyer, Megha Ram, David Rideout, Dongjin Song
High resolution population estimates from telecommunications data. EPJ Data Sci. 4 (1) (2015)
Dongjin Song, David A. Meyer
A model of consistent node types in signed directed social networks. ASONAM (2014)
Dongjin Song, David A. Meyer
A Model of Consistent Node Types in Signed Directed Social Networks. CoRR (2014)
Yongqi Lou, Dongjin Song
Design for the Public Usage of Rural Surplus Space (PURSS): The Case Study of DEISGN Harvests. HCI (19) (2014)
Dongjin Song, Dacheng Tao
Biologically Inspired Feature Manifold for Scene Classification. IEEE Trans. Image Process. 19 (1) (2010)
Dongjin Song, Dacheng Tao
Discrminative Geometry Preserving Projections. ICIP (2009)
Dongjin Song, Dacheng Tao
C1 units for scene classification. ICPR (2008)