People:
Randolf Scholz, M.Sc. Mathematics
Office hour:
C208 Spl, upon request
C208 Spl, upon request
Phone, Fax, Email:
Phone: | +49 5121 / 883-40370 |
Fax: | n.a. |
e-mail: | ![]() |
Postal address:
Information Systems and Machine Learning Lab
Universitätsplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Information Systems and Machine Learning Lab
Universitätsplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Publications:
- Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz (2022):
Multi-script handwritten digit recognition using multi-task learning., . - Dr. Nghia Duong-Trung, Stefan Born, JongWoo Kim, Marie-Therese Schermeyer, Katharina Paulick, Maxim Borisyak, Ernesto Martinez, Mariano Nicolas Cruz-Bournazou, Randolf Scholz, Lars Schmidt-Thieme, Peter Neubauer,, Thorben Werner (2022):
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development, Biochemical Engineering Journal . - Raaghav Radhakrishnan, Jan Fabian Schmid, Randolf Scholz, Lars Schmidt-Thieme (2021):
Deep Metric Learning for Ground Images, in arXiv preprint arXiv:2109.01569 (2021). - Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz (2022):
Multi-script handwritten digit recognition using multi-task learning., in J. Intell. Fuzzy Syst., pp. 355-364. - Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme (2019):
Learning surrogate losses, in arXiv preprint arXiv:1905.10108 (2019). - Lukas Brinkmeyer, Rafael Rêgo Drumond, Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme (2019):
Chameleon: Learning Model Initializations Across Tasks With Different Schemas, in arXiv preprint arXiv:1909.13576 (2019).