Dongjin Song

According to our database, Dongjin Song authored at least 81 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.

Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Y. Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan

IEEE Trans. Pattern Anal. Mach. Intell., October, 2024

Towards Safe Autonomy in Hybrid Traffic: Detecting Unpredictable Abnormal Behaviors of Human Drivers via Information Sharing.

Jiangwei Wang, Lili Su, Songyang Han, Dongjin Song, Fei Miao

ACM Trans. Cyber Phys. Syst., April, 2024

International Trade Flow Prediction with Bilateral Trade Provisions.

Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song

CoRR, 2024

Learning System Dynamics without Forgetting.

Xikun Zhang, Dongjin Song, Yushan Jiang, Yixin Chen, Dacheng Tao

CoRR, 2024

S²IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting.

Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song

CoRR, 2024

Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference.

Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song

CoRR, 2024

Structural Knowledge Informed Continual Multivariate Time Series Forecasting.

Zijie Pan, Yushan Jiang, Dongjin Song, Sahil Garg, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka

CoRR, 2024

Continual Learning on Graphs: Challenges, Solutions, and Opportunities.

Xikun Zhang, Dongjin Song, Dacheng Tao

CoRR, 2024

Rank Supervised Contrastive Learning for Time Series Classification.

Qianying Ren, Dongsheng Luo, Dongjin Song

CoRR, 2024

Topology-aware Embedding Memory for Learning on Expanding Graphs.

Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao

CoRR, 2024

Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements.

Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding

CoRR, 2024

A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System.

Lisha Ye, Jianfeng Zhou, Zhe Yin, Kunpeng Han, Haoyuan Hu, Dongjin Song

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs.

Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Foundation Models for Time Series Analysis: A Tutorial and Survey.

Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Topology-aware Embedding Memory for Continual Learning on Expanding Networks.

Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Empowering Time Series Analysis with Large Language Models: A Survey.

Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting.

Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Online GNN Evaluation Under Test-time Graph Distribution Shifts.

Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Collective Imaginaries for the Futures of Care Work.

Yiying Wu, Jung-Joo Lee, Ajit G. Pillai, Janghee Cho, Naseem Ahmadpour, Virpi Roto, Thida Sachathep, Jiashuo Liu, Mouna Sawan, Dongjin Song, Martina Caic, Lucas Cheng, Renxuan Liu, Sarah Kettley, Luis Soares, Kazjon Grace, Thomas Astell-Burt

Proceedings of the Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing, 2024

Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement.

Soumyashree Sahoo, Chinmaey Shende, Md. Zakir Hossain, Parit Patel, Xinyu Wang, Md Ishtyaq Mahmud, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang

Proceedings of the IEEE/ACM Conference on Connected Health: Applications, 2024

2023

Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data.

Chinmaey Shende, Soumyashree Sahoo, Stephen Sam, Parit Patel, Reynaldo Morillo, Xinyu Wang, Shweta Ware, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., September, 2023

Hierarchical Prototype Networks for Continual Graph Representation Learning.

Xikun Zhang, Dongjin Song, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis.

Yang Jiao, Kai Yang, Dongjin Song

CoRR, 2023

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.

Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan

CoRR, 2023

Tutorials at The Web Conference 2023.

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

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

The 9th SIGKDD International Workshop on Mining and Learning from Time Series.

Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation.

Yushan Jiang, Wenchao Yu, Dongjin Song, Lu Wang, Wei Cheng, Haifeng Chen

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles.

Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su

IROS, 2023

HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings.

Chang Li, Dongjin Song, Dacheng Tao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Asynchronous Distributed Bilevel Optimization.

Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Interpretable Skill Learning for Dynamic Treatment Regimes through Imitation.

Yushan Jiang, Wenchao Yu, Dongjin Song, Wei Cheng, Haifeng Chen

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

2022

TimeAutoAD: Autonomous Anomaly Detection With Self-Supervised Contrastive Loss for Multivariate Time Series.

Yang Jiao, Kai Yang, Dongjin Song, Dacheng Tao

IEEE Trans. Netw. Sci. Eng., 2022

Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series.

Jurijs Nazarovs, Cristian Lumezanu, Qianying Ren, Yuncong Chen, Takehiko Mizoguchi, Dongjin Song, Haifeng Chen

CoRR, 2022

Distributed Distributionally Robust Optimization with Non-Convex Objectives.

Yang Jiao, Kai Yang, Dongjin Song

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CGLB: Benchmark Tasks for Continual Graph Learning.

Xikun Zhang, Dongjin Song, Dacheng Tao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications.

Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Sparsified Subgraph Memory for Continual Graph Representation Learning.

Xikun Zhang, Dongjin Song, Dacheng Tao

Proceedings of the IEEE International Conference on Data Mining, 2022

Deep Federated Anomaly Detection for Multivariate Time Series Data.

Wei Zhu, Dongjin Song, Yuncong Chen, Wei Cheng, Bo Zong, Takehiko Mizoguchi, Cristian Lumezanu, Haifeng Chen, Jiebo Luo

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Inductive Contextual Relation Learning for Personalization.

Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla

ACM Trans. Inf. Syst., 2021

Unsupervised Document Embedding via Contrastive Augmentation.

Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang

CoRR, 2021

Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection.

Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection.

Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems.

Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, Yevgeniy Vorobeychik

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization.

Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Multi-Task Recurrent Modular Networks.

Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series.

Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan B. Davidson

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series.

Yang Jiao, Kai Yang, Shaoyu Dou, Pan Luo, Sijia Liu, Dongjin Song

CoRR, 2020

Node Classification in Temporal Graphs Through Stochastic Sparsification and Temporal Structural Convolution.

Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

At the Speed of Sound: Efficient Audio Scene Classification.

Bo Dong, Cristian Lumezanu, Yuncong Chen, Dongjin Song, Takehiko Mizoguchi, Haifeng Chen, Latifur Khan

Proceedings of the 2020 on International Conference on Multimedia Retrieval, 2020

Robust Graph Representation Learning via Neural Sparsification.

Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang

Proceedings of the 37th International Conference on Machine Learning, 2020

Inductive and Unsupervised Representation Learning on Graph Structured Objects.

Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjin Song, Haifeng Chen, Yun Fu

Proceedings of the 8th International Conference on Learning Representations, 2020

Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval.

Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series.

Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation.

Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep Co-Clustering.

Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Heterogeneous Graph Neural Network.

Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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.

Chang Li, Dongjin Song, Dacheng Tao

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.

Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning Deep Network Representations with Adversarially Regularized Autoencoders.

Wenchao Yu, Cheng Zheng, Wei Cheng, Charu C. Aggarwal, Dongjin Song, Bo Zong, Haifeng Chen, Wei Wang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep r -th Root of Rank Supervised Joint Binary Embedding for Multivariate Time Series Retrieval.

Dongjin Song, Ning Xia, Wei Cheng, Haifeng Chen, Dacheng Tao

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Detecting Low Rating Android Apps Before They Have Reached the Market.

Ding Li, Dongjin Song

CoRR, 2017

A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction.

Yao Qin, Dongjin Song, Haifeng Chen, Wei Cheng, Guofei Jiang, Garrison W. Cottrell

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Exemplar-centered Supervised Shallow Parametric Data Embedding.

Martin Renqiang Min, Hongyu Guo, Dongjin Song

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems.

Jingchao Ni, Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, Xiang Zhang

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Identifying and quantifying nonlinear structured relationships in complex manufactural systems.

Tingyang Xu, Tan Yan, Dongjin Song, Wei Cheng, Haifeng Chen, Geoff Jiang, Jinbo Bi

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

A Shallow High-Order Parametric Approach to Data Visualization and Compression.

Martin Renqiang Min, Hongyu Guo, Dongjin Song

CoRR, 2016

Fast Structural Binary Coding.

Dongjin Song, Wei Liu, David A. Meyer

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Efficient Robust Conditional Random Fields.

Dongjin Song, Wei Liu, Tianyi Zhou, Dacheng Tao, David A. Meyer

IEEE Trans. Image Process., 2015

Link sign prediction and ranking in signed directed social networks.

Dongjin Song, David A. Meyer

Soc. Netw. Anal. Min., 2015

High resolution population estimates from telecommunications data.

Rex W. Douglass, David A. Meyer, Megha Ram, David Rideout, Dongjin Song

EPJ Data Sci., 2015

Efficient Latent Link Recommendation in Signed Networks.

Dongjin Song, David A. Meyer, Dacheng Tao

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Top-k Link Recommendation in Social Networks.

Dongjin Song, David A. Meyer, Dacheng Tao

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Top Rank Supervised Binary Coding for Visual Search.

Dongjin Song, Wei Liu, Rongrong Ji, David A. Meyer, John R. Smith

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Design Process as Communication Agency for Value Co-Creation in Open Social Innovation Project: - A Case Study of QuYang Community in Shanghai.

Dongjin Song, Susu Nousala, Yongqi Lou

Proceedings of the Cross-Cultural Design Methods, Practice and Impact, 2015

Rank Preserving Hashing for Rapid Image Search.

Dongjin Song, Wei Liu, David A. Meyer, Dacheng Tao, Rongrong Ji

Proceedings of the 2015 Data Compression Conference, 2015

Recommending Positive Links in Signed Social Networks by Optimizing a Generalized AUC.

Dongjin Song, David A. Meyer

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Design for the Public Usage of Rural Surplus Space (PURSS): The Case Study of DEISGN Harvests.

Yongqi Lou, Dongjin Song

Proceedings of the Cross-Cultural Design, 2014

A model of consistent node types in signed directed social networks.

Dongjin Song, David A. Meyer

Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014

2010

Biologically Inspired Feature Manifold for Scene Classification.

Dongjin Song, Dacheng Tao

IEEE Trans. Image Process., 2010

2009

Discrminative Geometry Preserving Projections.

Dongjin Song, Dacheng Tao

Proceedings of the International Conference on Image Processing, 2009

2008

C1 units for scene classification.

Dongjin Song, Dacheng Tao

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008