publications

2024

Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data

Junjie Liang, Weijieying Ren, Hanifi Sahar, and 1 more author

In Proceedings of the AAAI Conference on Artificial Intelligence, 2024

Bib PDF Supp Slides

@inproceedings{liang2024inducing,
  title = {Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data},
  author = {Liang, Junjie and Ren, Weijieying and Sahar, Hanifi and Honavar, Vasant G},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {38},
  number = {12},
  pages = {13736--13743},
  year = {2024},
}

2021

Longitudinal deep kernel Gaussian process regression

Junjie Liang, Yanting Wu, Dongkuan Xu, and 1 more author

In Proceedings of the AAAI Conference on Artificial Intelligence, 2021

Bib PDF Supp Code Slides

@inproceedings{liang2021longitudinal,
  title = {Longitudinal deep kernel Gaussian process regression},
  author = {Liang, Junjie and Wu, Yanting and Xu, Dongkuan and Honavar, Vasant G},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {35},
  number = {10},
  pages = {8556--8564},
  year = {2021},
}

Unite: Uncertainty-based health risk prediction leveraging multi-sourced data

Chacha Chen, Junjie Liang, Fenglong Ma, and 3 more authors

In Proceedings of the Web Conference 2021, 2021

@inproceedings{chen2021unite,
  title = {Unite: Uncertainty-based health risk prediction leveraging multi-sourced data},
  author = {Chen, Chacha and Liang, Junjie and Ma, Fenglong and Glass, Lucas and Sun, Jimeng and Xiao, Cao},
  booktitle = {Proceedings of the Web Conference 2021},
  pages = {217--226},
  year = {2021},
}

Fare: Enabling fine-grained attack categorization under low-quality labeled data

Junjie Liang, Wenbo Guo, Tongbo Luo, and 3 more authors

In Proceedings of The Network and Distributed System Security Symposium (NDSS), 2021

@inproceedings{liang2021fare,
  title = {Fare: Enabling fine-grained attack categorization under low-quality labeled data},
  author = {Liang, Junjie and Guo, Wenbo and Luo, Tongbo and Vasant, Honavar and Wang, Gang and Xing, Xinyu},
  booktitle = {Proceedings of The Network and Distributed System Security Symposium (NDSS)},
  year = {2021},
}

Transformer-style relational reasoning with dynamic memory updating for temporal network modeling

Dongkuan Xu, Junjie Liang, Wei Cheng, and 3 more authors

In Proceedings of the AAAI Conference on Artificial Intelligence, 2021

@inproceedings{xu2021transformer,
  title = {Transformer-style relational reasoning with dynamic memory updating for temporal network modeling},
  author = {Xu, Dongkuan and Liang, Junjie and Cheng, Wei and Wei, Hua and Chen, Haifeng and Zhang, Xiang},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {35},
  number = {5},
  pages = {4546--4554},
  year = {2021},
}

How Do We Move: Modeling Human Movement with System Dynamics

Hua Wei, Dongkuan Xu, Junjie Liang, and 1 more author

In Proceedings of the AAAI Conference on Artificial Intelligence, 2021

@inproceedings{wei2021we,
  title = {How Do We Move: Modeling Human Movement with System Dynamics},
  author = {Wei, Hua and Xu, Dongkuan and Liang, Junjie and Li, Zhenhui Jessie},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {35},
  number = {5},
  pages = {4445--4452},
  year = {2021},
}

2020

LMLFM: longitudinal multi-level factorization machine

Junjie Liang, Dongkuan Xu, Yiwei Sun, and 1 more author

In Proceedings of the AAAI Conference on Artificial Intelligence, 2020

Bib PDF Supp Code

@inproceedings{liang2020lmlfm,
  title = {LMLFM: longitudinal multi-level factorization machine},
  author = {Liang, Junjie and Xu, Dongkuan and Sun, Yiwei and Honavar, Vasant},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {34},
  number = {04},
  pages = {4811--4818},
  year = {2020},
}

2018

A user similarity-based Top-N recommendation approach for mobile in-application advertising

Jinlong Hu, Junjie Liang, Yuezhen Kuang, and 1 more author

Expert Systems with Applications, 2018

@article{hu2018user,
  title = {A user similarity-based Top-N recommendation approach for mobile in-application advertising},
  author = {Hu, Jinlong and Liang, Junjie and Kuang, Yuezhen and Honavar, Vasant},
  journal = {Expert Systems with Applications},
  volume = {111},
  pages = {51--60},
  year = {2018},
  publisher = {Pergamon},
}

Top-N-rank: A scalable list-wise ranking method for recommender systems

Junjie Liang, Jinlong Hu, Shoubin Dong, and 1 more author

In 2018 IEEE International Conference on Big Data (Big Data), 2018

@inproceedings{liang2018top,
  title = {Top-N-rank: A scalable list-wise ranking method for recommender systems},
  author = {Liang, Junjie and Hu, Jinlong and Dong, Shoubin and Honavar, Vasant},
  booktitle = {2018 IEEE International Conference on Big Data (Big Data)},
  pages = {1052--1058},
  year = {2018},
  organization = {IEEE},
}

2017

iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection

Jinlong Hu, Junjie Liang, and Shoubin Dong

Mobile Information Systems, 2017

@article{hu2017ibgp,
  title = {iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection},
  author = {Hu, Jinlong and Liang, Junjie and Dong, Shoubin},
  journal = {Mobile Information Systems},
  year = {2017},
}