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Stephan Sloth Lorenzen
Stephan Sloth Lorenzen
ph.d. student, Department of Computer Science, University of Copenhagen
Verified email at di.ku.dk
Title
Cited by
Cited by
Year
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ...
Scientific reports 11 (1), 3246, 2021
802021
Second order PAC-Bayesian bounds for the weighted majority vote
A Masegosa, S Lorenzen, C Igel, Y Seldin
Advances in Neural Information Processing Systems 33, 5263-5273, 2020
382020
Tracking behavioral patterns among students in an online educational system
S Lorenzen, N Hjuler, S Alstrup
arXiv preprint arXiv:1908.08937, 2019
192019
On PAC-Bayesian bounds for random forests
SS Lorenzen, C Igel, Y Seldin
Machine Learning 108 (8-9), 1503-1522, 2019
152019
Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark
SS Lorenzen, M Nielsen, E Jimenez-Solem, TS Petersen, A Perner, ...
Scientific reports 11 (1), 18959, 2021
142021
Information bottleneck: Exact analysis of (quantized) neural networks
SS Lorenzen, C Igel, M Nielsen
arXiv preprint arXiv:2106.12912, 2021
112021
Revisiting wedge sampling for budgeted maximum inner product search
SS Lorenzen, N Pham
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
112020
Chebyshev-Cantelli PAC-Bayes-Bennett inequality for the weighted majority vote
YS Wu, A Masegosa, S Lorenzen, C Igel, Y Seldin
Advances in Neural Information Processing Systems 34, 12625-12636, 2021
102021
Detecting ghostwriters in high schools
M Stavngaard, A Sørensen, S Lorenzen, N Hjuler, S Alstrup
arXiv preprint arXiv:1906.01635, 2019
92019
On predicting student performance using low-rank matrix factorization techniques
S Lorenzen, N Pham, S Alstrup
European Conference on e-Learning, 326-334, 2017
82017
DABAI: A data driven project for e-Learning in Denmark
S Alstrup, C Hansen, C Hansen, N Hjuler, S Lorenzen, N Pham
European Conference on e-Learning, 18-24, 2017
62017
Steiner tree heuristics in Euclidean d-space
A Olsen, S Lorenzen, R Fonseca, P Winter
Proc. of the 11th DIMACS Implementation Challenge, 2014
62014
Online transfer learning with partial feedback
Z Kang, M Nielsen, B Yang, L Deng, SS Lorenzen
Expert Systems with Applications 212, 118738, 2023
42023
Investigating writing style development in high school
S Lorenzen, N Hjuler, S Alstrup
arXiv preprint arXiv:1906.03072, 2019
22019
Developing machine learning models for predicting intensive care unit resource use during the COVID-19 pandemic
SS Lorenzen, M Nielsen, E Jimenez-Solem, TS Petersen, A Perner, ...
medRxiv, 2021.03. 19.21253947, 2021
12021
Steiner Tree Heuristic in the Euclidean d-Space Using Bottleneck Distances
SS Lorenzen, P Winter
Experimental Algorithms: 15th International Symposium, SEA 2016, St …, 2016
12016
Assessing the Utility of Deep Neural Networks in Detecting Superficial Surgical Site Infections From Free Text Electronic Health Record Data
A Bonde, S Lorenzen, G Brixen, A Troelsen, M Sillesen
2023
Developing Machine Learning Models for Predicting Intensive Care Unit Resource Use During the COVID-19 Pandemic: Experiences from a Bi-Regional Health Care System Covering 2.5 …
SS Lorenzen, M Nielsen, E Jimenez-Solem, TS Petersen, A Perner, ...
2021
Learning from Educational Data
SS Lorenzen
School of The Faculty of Science, University of Copenhagen, 2019
2019
Bottleneck distances and Steiner trees in the Euclidean d-space
P Winter, SS Lorenzen
The European Workshop on Computational Geometry (EuroCG) 2016, 2016
2016
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