Dr. Kevin Alexander Laube
Research Interests
- Neural Architecture Search
- Neural Networks
- Hyper-parameter Optimization
Background
Since June 2018
Research assistant at the Department of Cognitive Systems, University of Tübingen
2016 - 2018
MSc in computer science, University of Tübingen
2012 - 2016
BSc in computer science, University of Furtwangen
Teaching
- Seminar: Current Topics in Deep Neural Networks (Winter 2021/22)
- Tutorial: Introduction to Neural Networks, (Summer 2021)
- Seminar: Optimization and Architecture Search of Deep Neural Networks, (Winter 2020/21)
- Tutorial: Introduction to Neural Networks, (Summer 2020)
- Tutorial: Deep Neural Networks, (Winter 2019/20)
- Tutorial: Introduction to Neural Networks, (Summer 2019)
- Tutorial: Einführung in die Technische Informatik, (Winter 2018/19)
Publications
[1] | Kevin Alexander Laube and Andreas Zell. "ShuffleNASNets: Efficient CNN models through modified Efficient Neural Architecture Search". In 2019 Internetional Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 2019. [DOI] [arxiv] |
[2] | Kevin Alexander Laube and Andreas Zell. "Prune and Replace NAS". In 2019 International Conference on Machine Learning and Applications (ICMLA), Boca Raton, Florida, USA, December 2019. [DOI] [arxiv] |
[3] | Kevin Alexander Laube and Andreas Zell. "Exploring single-path Architecture search ranking correlations", initially submitted to ICLR 2021 but abandoned due to many similar works appearing at the time and fundamental difficulties of a thorough empirical evaluation [openreview] |
[4] | Kevin Alexander Laube and Andreas Zell. "What to expect of hardware metric predictors in NAS", accepted at AutoML-Conf 2022. [openreview] |
[5] | Kevin Alexander Laube and Andreas Zell. "Conditional super-network weights", currently not submitted. [arxiv] |
[6] | Kevin Alexander Laube. "The UniNAS framework: combining modules in arbitrarily complex configurations with argument trees" [arxiv] [github] |