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Efficient Machine Learning, Computer Vision, Diffusion Models, Large Language Models, Neural Architecture Search
Canada

Biography

Keith G. Mills is a PhD Candidate at the Department of Electrical and Computer Engineering at the University of Alberta under the supervision of Professor Di Niu. He received his MSc. in Computer Engineering from the University of Alberta in 2020 and his BSc. in Computer Engineering, with Distinction, and also from the University of Alberta in 2018. Concurrently, he is an Associate Research Intern at Edmonton Research Center for Huawei Technologies Canada Co., Ltd., where his current research focus is Neural Architecture Search for Efficient Machine Learning.

Activities

Employment (1)

Huawei Technologies Co Ltd Canada: Edmont, AB, CA

2019-11-04 to present | Associate Researcher, Intern (HiSilicon)
Employment
Source: Self-asserted source
Keith G. Mills

Education and qualifications (3)

University of Alberta: Edmonton, Alberta, CA

2021-01-04 to present | Ph.D. Software Engineering and Intelligent Systems (Department of Electrical and Computer Engineering)
Education
Source: Self-asserted source
Keith G. Mills

University of Alberta: Edmonton, Alberta, CA

2018-09-01 to 2020-12-23 | MSc. Computer Engineering (Department of Electrical and Computer Engineering)
Education
Source: Self-asserted source
Keith G. Mills

University of Alberta: Edmonton, Alberta, CA

2014-09-01 to 2018-06-13 | BSc. Computer Engineering (Department of Electrical and Computer Engineering)
Education
Source: Self-asserted source
Keith G. Mills

Professional activities (4)

IEEE Computer Society: Washington, US

2024 to present | Professional Member
Membership
Source: Self-asserted source
Keith G. Mills

Association for the Advancement of Artificial Intelligence: Palo Alto, US

2023 to present | Student Member
Membership
Source: Self-asserted source
Keith G. Mills

Association for Computing Machinery: New York, US

2021 to present | Student Member
Membership
Source: Self-asserted source
Keith G. Mills

Association of Professional Engineers Geologists and Geophysicists of Alberta: Edmonton, AB, CA

2018-10-31 to present | Engineer-in-Training
Membership
Source: Self-asserted source
Keith G. Mills

Funding (1)

A Data-Driven, Explainable Approach to Generate Better, Faster and More Efficient Neural Networks

2024-01 to 2024-12 | Award
Alberta Innovates (Edmonton, Alberta, CA)
Source: Self-asserted source
Keith G. Mills

Works (14)

Qua$^2$SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models

2025-02-25 | Conference paper
Contributors: Keith G. Mills; Mohammad Salameh; Ruichen Chen; Negar Hassanpour; Wei Lu; Di Niu
Source: Self-asserted source
Keith G. Mills

EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time

Proceedings of the 41st International Conference on Machine Learning
2024 | Conference paper
URI:

https://proceedings.mlr.press/v235/lu24g.html

Contributors: Lu, Shengyao; Liu, Bang; Mills, Keith G; He, Jiao; Niu, Di; Salakhutdinov, Ruslan; Kolter, Zico; Heller, Katherine; Weller, Adrian; Oliver, Nuria et al.
Source: Self-asserted source
Keith G. Mills

Building Optimal Neural Architectures using Interpretable Knowledge

The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024
2024-06-19 | Conference paper
Contributors: Keith G. Mills; Fred X. Han; Mohammad Salameh; Shengyao Lu; Chunhua Zhou; Jiao He; Fengyu Sun; Di Niu
Source: Self-asserted source
Keith G. Mills

GOAt: Explaining Graph Neural Networks via Graph Output Attribution

2024-01-16 | Conference paper
Contributors: Shengyao Lu; Keith G. Mills; Jiao He; Bang Liu; Di Niu
Source: Self-asserted source
Keith G. Mills

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution

Advances in Neural Information Processing Systems
2023-12-14 | Conference paper
URI:

https://proceedings.neurips.cc/paper_files/paper/2023/file/eb5d9195b201ec7ba66c8e20b396d349-Paper-Conference.pdf

Contributors: Salameh, Mohammad; Mills, Keith; Hassanpour, Negar; Han, Fred; Zhang, Shuting; Lu, Wei; Jui, Shangling; ZHOU, CHUNHUA; Sun, Fengyu; Niu, Di et al.
Source: Self-asserted source
Keith G. Mills

AIO-P: Expanding Neural Performance Predictors Beyond Image Classification

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)
2023-06-27 | Conference paper
Contributors: Keith G. Mills; Di Niu; Mohammad Salameh; Weichen Qiu; Fred X. Han; Puyuan Liu; Jialin Zhang; Wei Lu; Shangling Jui
Source: Self-asserted source
Keith G. Mills

GENNAPE: Towards Generalized Neural Architecture Performance Estimators

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)
2023-06-27 | Conference paper
Contributors: Keith G. Mills; Fred X. Han; Jialin Zhang; Fabian Chudak; Ali Safari Mamaghani; Mohammad Salameh; Wei Lu; Shangling Jui; Di Niu
Source: Self-asserted source
Keith G. Mills

A General-Purpose Transferable Predictor for Neural Architecture Search

Proceedings of the 2023 SIAM International Conference on Data Mining (SDM)
2023-04-12 | Conference paper
Part of ISBN: 9781611977653
Contributors: Fred X. Han; Keith G. Mills; Fabian Chudak; Parsa Riahi; Mohammad Salameh; Jialin Zhang; Wei Lu; Shangling Jui; Di Niu
Source: Self-asserted source
Keith G. Mills

R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning.

Proceedings of the Tenth International Conference on Learning Representations (ICLR'22)
2022-04-25 | Conference paper
Contributors: Shengyao Lu; Bang Liu; Keith G. Mills; Shangling Jui; Di Niu
Source: Self-asserted source
Keith G. Mills

Exploring Neural Architecture Search Space via Deep Deterministic Sampling

IEEE Access
2021 | Journal article
Contributors: Keith G. Mills; Mohammad Salameh; Di Niu; Fred X. Han; Seyed Saeed Changiz Rezaei; Hengshuai Yao; Wei Lu; Shuo Lian; Shangling Jui
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L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning

Proceedings of the 30th ACM International Conference on Information & Knowledge Management
2021-10-26 | Conference paper
Contributors: Keith G. Mills; Fred X. Han; Mohammad Salameh; Seyed Saeed Changiz Rezaei; Linglong Kong; Wei Lu; Shuo Lian; Shangling Jui; Di Niu
Source: Self-asserted source
Keith G. Mills

Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search

Proceedings of the 30th ACM International Conference on Information & Knowledge Management
2021-10-26 | Conference paper
Contributors: Keith G. Mills; Fred X. Han; Jialin Zhang; Seyed Saeed Changiz Rezaei; Fabian Chudak; Wei Lu; Shuo Lian; Shangling Jui; Di Niu
Source: Self-asserted source
Keith G. Mills

Generative Adversarial Neural Architecture Search

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21)
2021-05-19 | Conference paper
Contributors: Seyed Saeed Changiz Rezaei; Fred X. Han; Di Niu; Mohammad Salameh; Keith G. Mills; Shuo Lian; Wei Lu; Shangling Jui
Source: Self-asserted source
Keith G. Mills

Android Malware Detection Based on Factorization Machine

IEEE Access
2019 | Journal article
Contributors: Chenglin Li; Keith Mills; Di Niu; Rui Zhu; Hongwen Zhang; Husam Kinawi
Source: check_circle
Crossref