Researcher Data Analysis SystemsPhone: +43 50 343 853 Ramin.Nikzad-Langerodi@scch.at Data Science - DAS
R. Nikzad-Langerodi, W. Zellinger, S. Saminger-Platz, B. Moser. Domain adaptation for regression under Beer–Lambert’s law. Knowledge-Based Systems, volume 210, DOI: 10.1016/j.knosys.2020.106447, December, 2020.
R. Nikzad-Langerodi, B. Moser, W. Zellinger, S. Saminger-Platz. Domain-invariant regression under Beer-Lambert’s Law. In M. Wani, T. Khoshgoftaar, D. Wang, H. Wang, N. Seliya (editors), Proceedings of the 18th IEEE International Conference of Machine Learning and Applications (ICMLA 2019), pages 581-856, DOI 10.1109/ICMLA.2019.00108,, IEEE, February, 2020.
R. Nikzad-Langerodi, F. Sobiedzky. Graph‐based calibration transfer. Journal of Chemometrics, volume e3319, DOI: 10.1002/cem.3319, November, 2020.
P. Mishra, R. Nikzad-Langerodi. Partial least square regression versus domain invariant partial least square regression with application to near-infrared spectroscopy of fresh fruit. Infrared Physics & Technology, DOI: 10.1016/j.infrared.2020.103547, October, 2020.
E. Lughofer, R. Nikzad-Langerodi. Robust generalized fuzzy systems training from high-dimensional time-series data using local structure preserving PLS. IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2019.2945535, October, 2019.
