Refereed Conference Proceedings

Shengyao Lu, Bang Liu, Keith G. Mills, Jiao He and Di Niu. “EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time”, accepted to the Forty-first International Conference on Machine Learning (ICML’24; 27.5% acceptance rate).

Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun and Di Niu. “Building Optimal Neural Architectures using Interpretable Knowledge”, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’24; 23.6% acceptance rate), pages 5726-5735.
[Poster][Video][Slides]

Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu and Di Niu. “GOAt: Explaining Graph Neural Networks via Graph Output Attribution”, published in the 12th International Conference on Learning Representations (ICLR 2024; 31.0% acceptance rate).
[Poster][Video][Slides]

Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun and Di Niu. “AutoGO: Automated Computation Graph Optimization for Neural Network Evolution.” In Advances in Neural Information Processing Systems (NeurIPS 2023; 26.1% acceptance rate), vol. 36, pages 74455-74477.
[Poster][Video][Slides]

Fred X. Han, Keith G. Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui and Di Niu. “A General-Purpose Transferable Predictor for Neural Architecture Search.” In Proceedings of the 2023 SIAM International Conference on Data Mining (SDM23; 27.4% acceptance rate), pages 721-729.
[Poster][Slides]

Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu and Shangling Jui. “AIO-P: Expanding Neural Performance Predictors Beyond Image Classification.” In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23; 19.6% acceptance rate), pages 9180-9189.
Selected for oral presentation
[Poster][Video][Slides]

Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari Mamaghani, Mohammad Salameh, Wei Lu, Shangling Jui and Di Niu. “GENNAPE: Towards Generalized Neural Architecture Performance Estimators.” In Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23; 19.6% acceptance rate), pages 9190-9199.
Selected for oral presentation
[Poster][Video][Slides]

Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui and Di Niu. “R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning,” published in the 10th International Conference on Learning Representations (ICLR 2022; 32.9% acceptance rate).
Spotlight paper
[Video]

Keith G. Mills, Fred X. Han, Jialin Zhang, Seyed Saeed Changiz Rezaei, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. “Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search.” In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM ‘21; 23.8% acceptance rate) as an Applied Research Paper, pages 4026-4035.
Selected for oral presentation
[Poster][Video][Slides]

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui and Di Niu. “L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.” In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM ‘21; 21.7% acceptance rate), pages 1284-1293.
Selected for oral presentation
[Poster][Video][Slides]

Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith Mills, Shuo Lian, Wei Lu and Shangling Jui. “Generative Adversarial Neural Architecture Search.” In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21; 13.9% acceptance rate), pages 2227-2234.
[Videos and Slides]

Refereed Journal Publications

Keith G. Mills, Mohammad Salameh, Di Niu, Fred X. Han, Seyed Saeed Changiz Rezaei, Hengshuai Yao, Wei Lu, Shuo Lian and Shangling Jui. “Exploring Neural Architecture Search Space via Deep Deterministic Sampling,” published in IEEE Access, Vol. 9 (2021), pages 110962-110974.

Chenglin Li, Keith Mills, Rui Zhu, Di Niu, Hongwen Zhang and Husam Kinawi. “Android Malware Detection based on Factorization Machine,” published in IEEE Access, Vol. 7 (2019), pages 184008-184019.

Poster Presentations

Keith G. Mills, Muhammad Fetrat Qharabagh, Weichen Qiu, Fred X. Han, Mohammad Salameh, Wei Lu, Shangling Jui and Di Niu. “Applying Graph Explanation to Operator Fusion,” presented as a Work-In-Progress (WIP) poster at the 60th ACM/EDAC/IEEE Design Automation Conference (DAC 2023) in San Francisco on July 12th, 2023.