Keith G. Mills, Mohammad Salameh, Ruichen Chen, Negar Hassanpour, Wei Lu and Di Niu.
“Qua2SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models”. In Proceedings
of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI-25).
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).
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).
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).
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).
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).
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).
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).
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).
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).
2025: George Walker Award for Best Doctoral Thesis
2024: Alberta Innovates Graduate Student Scholarship
2023/2022: Floyd Derkat Graduate Award in Artificial Intelligence and Machine Learning
2022/2019: Alberta Graduate Excellence Scholarship
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