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• 2018

  Addressing task heterogeneity in social media analytics

  Nelakurthi, A. R. & He, J., Jan 1 2018.

  Research output: Contribution to conference › Paper › peer-review
• 2020

  Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting

  Zhou, D., Zheng, L., Zhu, Y., Li, J. & He, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 2230-2240 11 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Neural networks
  • Finance
  • Time series analysis
  • Financial markets
  • Deep neural networks

• Complex heterogeneity learning: A theoretical and empirical study

  Yang, P., Tan, Q. & He, J., Nov 2020, In: Pattern Recognition. 107, 107519.

  Research output: Contribution to journal › Article › peer-review

  • Labeling
  • Image analysis
  • Quality control
  • Brain
• 2016

  Crowdsourcing via tensor augmentation and completion

  Zhou, Y. & He, J., Jan 1 2016, In: IJCAI International Joint Conference on Artificial Intelligence. 2016-January, p. 2435-2441 7 p.

  Research output: Contribution to journal › Conference article › peer-review

  • Crowdsourcing
  • Tensors
  • Labels
  • Labeling
  • Costs

• Discussion of ‘Reinforcement learning behaviors in sponsored search’

  He, J., May 1 2016, In: Applied Stochastic Models in Business and Industry. 32, 3, 1 p.

  Research output: Contribution to journal › Comment/debate › peer-review

• A Generalized Hierarchical Multi-Latent Space Model for Heterogeneous Learning

  Yang, P., Davulcu, H., Zhu, Y. & He, J., Dec 1 2016, In: IEEE Transactions on Knowledge and Data Engineering. 28, 12, p. 3154-3168 15 p., 7572203.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Labels
  • Image annotation
  • Genes
  • Learning algorithms
  • Tuning
• 2018

  RCLens: Interactive Rare Category Exploration and Identification

  Lin, H., Gao, S., Gotz, D., Du, F., He, J. & Cao, N., Jul 1 2018, In: IEEE Transactions on Visualization and Computer Graphics. 24, 7, p. 2223-2237 15 p.

  Research output: Contribution to journal › Article › peer-review

  • Problem-Based Learning
  • Visualization
  • Network security
  • Medicine
  • Learning algorithms
• 2020

  Generic Outlier Detection in Multi-Armed Bandit

  Ban, Y. & He, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 913-923 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Anomaly detection
  • Finance
  • Marketing
  • Set theory
  • Costs
• 2017

  Functional regression with mode-sparsity constraint

  Yang, P. & He, J., Jan 31 2017, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Bonchi, F., Wu, X., Baeza-Yates, R., Domingo-Ferrer, J. & Zhou, Z-H. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1311-1316 6 p. 7837991. (Proceedings - IEEE International Conference on Data Mining, ICDM).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Sensor networks
• 2018

  Heterogeneous representation learning with separable structured sparsity regularization

  Yang, P., Tan, Q., Zhu, Y. & He, J., Jun 1 2018, In: Knowledge and Information Systems. 55, 3, p. 671-694 24 p.

  Research output: Contribution to journal › Article › peer-review

  • Labels
• 2017

  HiDDen: Hierarchical dense subgraph detection with application to financial fraud detection

  Zhang, S., Zhou, D., Yildirim, M. Y., Alcorn, S., He, J., Davulcu, H. & Tong, H., 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. Chawla, N. & Wang, W. (eds.). Society for Industrial and Applied Mathematics Publications, p. 570-578 9 p. (Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Quadratic programming

• Discovering rare categories from graph streams

  Zhou, D., Karthikeyan, A., Wang, K., Cao, N. & He, J., Mar 1 2017, In: Data Mining and Knowledge Discovery. 31, 2, p. 400-423 24 p.

  Research output: Contribution to journal › Article › peer-review

  • Labeling
  • Sensor networks
  • Data mining
  • Wireless networks
  • Costs
• 2018

  Function-on-function regression with mode-sparsity regularization

  Yang, P., Tan, Q. & He, J., Mar 2018, In: ACM Transactions on Knowledge Discovery from Data. 12, 3, 36.

  Research output: Contribution to journal › Article › peer-review

  • Tensors
  • Sensor networks
• 2017

  A randomized approach for crowdsourcing in the presence of multiple views

  Zhou, Y. & He, J., Dec 15 2017, Proceedings - 17th IEEE International Conference on Data Mining, ICDM 2017. Karypis, G., Alu, S., Raghavan, V., Wu, X. & Miele, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 685-694 10 p. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2017-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Crowdsourcing
  • Iterative methods
  • Tensors

• Learning from data heterogeneity: Algorithms and applications

  He, J., 2017, 26th International Joint Conference on Artificial Intelligence, IJCAI 2017. Sierra, C. (ed.). International Joint Conferences on Artificial Intelligence, p. 5126-5130 5 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 0).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Crowdsourcing
  • Big data
• 2020

  InFoRM: Individual Fairness on Graph Mining

  Kang, J., He, J., MacIejewski, R. & Tong, H., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 379-389 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Costs
• 2017

  Learning from multi-modality multi-resolution data: An optimization approach

  Zhu, Y., Li, J. & He, J., 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. Chawla, N. & Wang, W. (eds.). Society for Industrial and Applied Mathematics Publications, p. 714-722 9 p. (Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Smelting
  • Aluminum
  • Time series
  • Temperature
• 2018

  Unlearn what you have learned: Adaptive crowd teaching with exponentially decayed memory learners

  Zhou, Y., Nelakurthi, A. R. & He, J., Jul 19 2018, KDD 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2817-2826 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Teaching
  • Crowdsourcing
  • Data storage equipment
  • Labels
  • Computer aided instruction

• Feature co-shrinking for co-clustering

  Tan, Q., Yang, P. & He, J., May 2018, In: Pattern Recognition. 77, p. 12-19 8 p.

  Research output: Contribution to journal › Article › peer-review

  • Feature extraction
  • Factorization
• 2017

  User-guided cross-domain sentiment classification

  Nelakurthi, A. R., Tong, H., MacIejewski, R., Bliss, N. & He, J., 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. Chawla, N. & Wang, W. (eds.). Society for Industrial and Applied Mathematics Publications, p. 471-479 9 p. (Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Sentiment analysis
  • Human engineering
  • Monitoring
  • Computer simulation
  • Experiments
• 2018

  Optimizing the wisdom of the crowd: Inference, learning, and teaching

  Zhou, Y. & He, J., Jan 1 2018.

  Research output: Contribution to conference › Paper › peer-review

• Should patients with diabetes be encouraged to integrate social media into their care plan?

  Nelakurthi, A. R., Pinto, A. M., Cook, C. B., Jones, L., Boyle, M., Ye, J., Lappas, T. & He, J., Jan 1 2018, In: Future Science OA. 4, 7, FSO323.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Social Media
  • Diabetes Mellitus
  • Social Networking
  • Self-Management
  • Life Style
• 2017

  Finding cut from the same cloth: Cross network link recommendation via joint matrix factorization

  Nelakurthi, A. R. & He, J., Jan 1 2017, p. 1467-1473. 7 p.

  Research output: Contribution to conference › Paper › peer-review

  • Factorization
  • Medical problems
  • Experiments
• 2016

  Co-clustering structural temporal data with applications to semiconductor manufacturing

  Zhu, Y. & He, J., May 2016, In: ACM Transactions on Knowledge Discovery from Data. 10, 4, 43.

  Research output: Contribution to journal › Article › peer-review

  • Semiconductor materials
  • Time series
  • Struts
  • Anomaly detection
  • Flow of gases
• 2020

  Local Motif Clustering on Time-Evolving Graphs

  Fu, D., Zhou, D. & He, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 390-400 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Seed
  • Complex networks
  • Experiments

• RCAnalyzer: visual analytics of rare categories in dynamic networks

  Pan, J. C., Han, D. M., Guo, F. Z., Zhou, D. W., Cao, N., He, J. R., Xu, M. L. & Chen, W., Apr 1 2020, In: Frontiers of Information Technology and Electronic Engineering. 21, 4, p. 491-506 16 p.

  Research output: Contribution to journal › Article › peer-review

  • Visualization
  • Labels
• 2018

  E-tail product return prediction via hypergraph-based local graph cut

  Li, J., He, J. & Zhu, Y., Jul 19 2018, KDD 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 519-527 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Electronic commerce
  • Freight transportation
  • Logistics
  • Data mining
  • Costs
• 2017

  Multi-task function-on-function regression with co-grouping structured sparsity

  Yang, P., Tan, Q. & He, J., Aug 13 2017, KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 1255-1264 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; vol. Part F129685).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2020

  Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective

  Nelakurthi, A. R. & He, J., Jan 16 2020, CRC Press. 98 p.

  Research output: Book/Report/Conference proceeding › Book

  • Machine learning
  • Communication
• 2017

  Local algorithm for user action prediction towards display ads

  Yang, H., Zhu, Y. & He, J., Aug 13 2017, KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 2091-2099 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; vol. Part F129685).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Display devices
  • Marketing
  • Computational complexity

• HiMuV: Hierarchical framework for modeling multi-modality multi-resolution data

  Li, J., He, J. & Zhu, Y., Dec 15 2017, Proceedings - 17th IEEE International Conference on Data Mining, ICDM 2017. Karypis, G., Alu, S., Raghavan, V., Wu, X. & Miele, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 267-276 10 p. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2017-November).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Smelting
  • Financial markets
  • Aluminum
  • Electric current control
  • Alumina

• Bi-Level rare temporal pattern detection

  Zhou, D., He, J. R., Cao, Y. & Seo, J. S., Jan 31 2017, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Bonchi, F., Wu, X., Baeza-Yates, R., Domingo-Ferrer, J. & Zhou, Z-H. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 719-728 10 p. 7837896. (Proceedings - IEEE International Conference on Data Mining, ICDM).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Anomaly detection
  • Electrocardiography
  • Labels
  • Sensor networks
  • Wireless networks

• A local algorithm for structure-preserving graph cut

  Zhou, D., Zhang, S., Yildirim, M. Y., Alcorn, S., Tong, H., Davulcu, H. & He, J., Aug 13 2017, KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 655-664 10 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; vol. Part F129685).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Proteins
  • Seed
  • Stars
  • Markov processes
  • Clustering algorithms
• 2018

  A local algorithm for product return prediction in E-commerce

  Zhu, Y., Li, J., He, J., Quanz, B. L. & Deshpande, A. A., Jul 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 3718-3724 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2018-July).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • History
  • Electronic commerce
  • Computational complexity
  • Set theory
  • Industry
• 2016

  Jointly modeling label and feature heterogeneity in medical informatics

  Yang, P., Yang, H., Fu, H., Zhou, D., Ye, J., Lappas, T. & He, J., May 2016, In: ACM Transactions on Knowledge Discovery from Data. 10, 4, 39.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Medical informatics
  • Labels
  • Classifiers
  • Data handling
  • Medical problems
• 2020

  Visual Analytics of Anomalous User Behaviors: A Survey

  Shi, Y., Liu, Y., Tong, H., He, J., Yan, G. & Cao, N., 2020, (Accepted/In press) In: IEEE Transactions on Big Data.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • User Behavior
  • Research Work
  • Financial Fraud
  • Financial Networks
  • Information technology

• Missing information imputation for disease-dedicated social networks with heterogeneous auxiliary data

  Liu, X., He, J., Min, W. & Yang, H., Apr 2 2020, In: IISE Transactions on Healthcare Systems Engineering. 10, 2, p. 87-98 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Social Networking
  • Heterogeneous networks
  • Biomarkers
  • social network
  • Medical problems
• 2016

  A graph-based hybrid framework for modeling complex heterogeneity

  Yang, P. & He, J., Jan 5 2016, Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. Aggarwal, C., Zhou, Z-H., Tuzhilin, A., Xiong, H. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1081-1086 6 p. 7373439. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2016-January).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Image analysis
  • Quality control
  • Brain
  • Set theory
• 2017

  Heterogeneous representation learning with structured sparsity regularization

  Yang, P. & He, J., Jan 31 2017, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016. Bonchi, F., Wu, X., Baeza-Yates, R., Domingo-Ferrer, J. & Zhou, Z-H. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 539-548 10 p. 7837878. (Proceedings - IEEE International Conference on Data Mining, ICDM).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Labels
  • Iterative methods
  • Learning systems
• 2016

  Rare category detection on time-evolving graphs

  Zhou, D., Wang, K., Cao, N. & He, J., Jan 5 2016, Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. Aggarwal, C., Zhou, Z-H., Tuzhilin, A., Xiong, H. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1135-1140 6 p. 7373448. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2016-January).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Labeling
  • Data mining
  • Costs
• 2018

  SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization

  Zhou, D., He, J. R., Yang, H. & Fan, W., Aug 2018, p. 2807-2816.

  Research output: Contribution to conference › Paper › peer-review

  • Labels
  • Curricula
  • Intrusion detection
  • Computer networks
  • Machinery
• 2017

  Towards optimal connectivity on multi-layered networks

  Chen, C., He, J., Bliss, N. & Tong, H., Oct 1 2017, In: IEEE Transactions on Knowledge and Data Engineering. 29, 10, p. 2332-2346 15 p., 7956273.

  Research output: Contribution to journal › Article › peer-review

  • Critical infrastructures
  • Biological systems
  • Cyber Physical System
  • Large scale systems
  • Set theory
• 2018

  Inferring Anchor Links Based on Social Network Structure

  Feng, S., Shen, D., Nie, T., Kou, Y., He, J. & Yu, G., Mar 8 2018, In: IEEE Access. 6, p. 17340-17353 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Anchors
  • Experiments
• 2016

  On the connectivity of multi-layered networks: Models, measures and optimal control

  Chen, C., He, J., Bliss, N. & Tong, H., Jan 5 2016, Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. Aggarwal, C., Zhou, Z-H., Tuzhilin, A., Xiong, H. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 715-720 6 p. 7373378. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2016-January).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Critical infrastructures
  • Flexible structures
  • Cyber Physical System
  • Network layers
  • Data structures
• 2018

  A winners-take-all incentive mechanism for crowd-powered systems

  Jiang, P., Wang, W., Ying, L., Zhou, Y. & He, J., Jun 18 2018, Proceedings of NetEcon 2018: The 13th Workshop on the Economics of Networks, Systems, and Computation - In conjunction with ACM SIGMETRICS 2018: The ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery, Inc, 3. (Proceedings of NetEcon 2018: The 13th Workshop on the Economics of Networks, Systems, and Computation - In conjunction with ACM SIGMETRICS 2018: The ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Crowdsourcing
  • Data Analytics
  • Data privacy
  • Big data
  • Cost functions
• 2020

  A Data-Driven Graph Generative Model for Temporal Interaction Networks

  Zhou, D., Zheng, L., Han, J. & He, J., Aug 23 2020, KDD 2020 - Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, p. 401-411 11 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Discriminators
  • Social sciences
  • Anomaly detection
  • Sampling
• 2017

  MultiC²: An Optimization framework for learning from task and worker dual heterogeneity

  Zhou, Y., Ying, L. & He, J., 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. Chawla, N. & Wang, W. (eds.). Society for Industrial and Applied Mathematics Publications, p. 579-587 9 p. (Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Crowdsourcing
  • Tensors
  • Labels
  • Entropy
  • Computational complexity
• 2020

  Crowd Teaching with Imperfect Labels

  Zhou, Y., Nelakurthi, A. R., MacIejewski, R., Fan, W. & He, J., Apr 20 2020, The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020. Association for Computing Machinery, Inc, p. 110-121 12 p. (The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Teaching
  • Labels
  • Labeling
  • Crowdsourcing
  • Gages

• A View-Adversarial Framework for Multi-View Network Embedding

  Fu, D., Xu, Z., Li, B., Tong, H. & He, J., Oct 19 2020, CIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, p. 2025-2028 4 p. (International Conference on Information and Knowledge Management, Proceedings).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Node
  • Anomaly Detection
  • Facebook
  • Comprehensiveness
  • Robustness
• 2016

  Comparing random forest with logistic regression for predicting class-imbalanced civil war onset data

  Muchlinski, D., Siroky, D., He, J. R. & Kocher, M., Dec 1 2016, In: Political Analysis. 24, 1, p. 87-103 17 p.

  Research output: Contribution to journal › Article › peer-review

  • civil war
  • logistics
  • regression
  • event
  • statistical method