Publications

Milad Alshomary, Timon Gurcke, Shahbaz Syed, Philipp Heinisch, Maximilian Spliethöver, Philipp Cimiano, Martin Potthast, und Henning Wachsmuth. Key Point Analysis via Contrastive Learning and Extractive Argument Summarization. In Khalid Al-Khatib, Yufang Hou, und Manfred Stede (Hrsg.), 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP, 184--189, Association for Computational Linguistics, November 2021. [PUMA: Analysis Argument Contrastive Extractive Key Point Summarization zno learning]

Suryanarayana Maddu, Bevan L. Cheeseman, Ivo F. Sbalzarini, und Christian L. Müller. Stability selection enables robust learning of partial differential equations from limited noisy data. arXiv, 2019. [PUMA: (cs.LG) (math.NA) (physics.data-an) Analysis Computer FOS Mathematics Numerical Physical Probability Statistics data information learning machine sciences xack] URL

Pascal Kerschke, und Heike Trautmann. Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning. Evol. Comput., (27)1:99--127, MIT Press, 2019. [PUMA: algorithm analysis black-box continuous exploratory landscape learning machine optimization selection single-objective zno automated]

Pascal Kerschke, Holger H Hoos, Frank Neumann, und Heike Trautmann. Automated algorithm selection: Survey and perspectives. Evol. Comput., (27)1:3--45, MIT Press, 2019. [PUMA: algorithm analysis approaches automated combinatorial configuration continuous data exploratory feature-based landscape learning machine metalearning optimisation selection streams zno]

Akshay Akshay, Mitali Katoch, Navid Shekarchizadeh, Masoud Abedi, Ankush Sharma, Fiona C Burkhard, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)Januar 2024. [PUMA: AutoML analysis classification data learning machine problems topic_federatedlearn visualization xack yaff]

Akshay Akshay, Mitali Katoch, Masoud Abedi, Navid Shekarchizadeh, Mustafa Besic, Fiona C Burkhard, Alex Bigger-Allen, Rosalyn M Adam, Katia Monastyrskaya, und Ali Hashemi Gheinani. SpheroScan: a user-friendly deep learning tool for spheroid image analysis. Gigascience, (12)Oxford University Press (OUP), Dezember 2022. [PUMA: 3D Image Mask R-CNN analysis deep high-throughput image learning screening segmentation spheroids topic_federatedlearn xack yaff]