Seuraa
Christina Göpfert
Christina Göpfert
Applied Scientist at Amazon
Vahvistettu sähköpostiosoite verkkotunnuksessa amazon.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Statistical mechanics of on-line learning under concept drift
M Straat, F Abadi, C Göpfert, B Hammer, M Biehl
Entropy 20 (10), 775, 2018
302018
When can unlabeled data improve the learning rate?
C Göpfert, S Ben-David, O Bousquet, S Gelly, I Tolstikhin, R Urner
Conference on Learning Theory, 2019, 25-28 June 2019, Phoenix, AZ, USA 99 …, 2019
282019
Time series prediction for graphs in kernel and dissimilarity spaces
B Paaßen, C Göpfert, B Hammer
Neural Processing Letters 48 (2), 669-689, 2018
192018
Interpretation of linear classifiers by means of feature relevance bounds
C Göpfert, L Pfannschmidt, JP Göpfert, B Hammer
Neurocomputing 298, 69-79, 2018
172018
Supervised learning in the presence of concept drift: a modelling framework
M Straat, F Abadi, Z Kan, C Göpfert, B Hammer, M Biehl
Neural Computing and Applications 34 (1), 101-118, 2022
132022
Discovering personalized semantics for soft attributes in recommender systems using concept activation vectors
C Göpfert, Y Chow, C Hsu, I Vendrov, T Lu, D Ramachandran, C Boutilier
Proceedings of the ACM Web Conference 2022, 2411-2421, 2022
122022
Differential privacy for learning vector quantization
J Brinkrolf, C Göpfert, B Hammer
Neurocomputing 342, 125-136, 2019
122019
Gaussian process prediction for time series of structured data.
B Paassen, C Göpfert, B Hammer
ESANN, 2016
112016
Feature relevance bounds for linear classification
C Göpfert, L Pfannschmidt, B Hammer
Proceedings of the ESANN, 24th European Symposium on Artificial Neural …, 2017
102017
FRI-Feature relevance intervals for interpretable and interactive data exploration
L Pfannschmidt, C Göpfert, U Neumann, D Heider, B Hammer
2019 IEEE Conference on Computational Intelligence in Bioinformatics and …, 2019
82019
Local reject option for deterministic multi-class SVM
J Kummert, B Paassen, J Jensen, C Göpfert, B Hammer
Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016
72016
Adversarial robustness curves
C Göpfert, JP Göpfert, B Hammer
Machine Learning and Knowledge Discovery in Databases: International …, 2020
52020
Prototype-based classifiers in the presence of concept drift: A modelling framework
M Biehl, F Abadi, C Göpfert, B Hammer
International Workshop on Self-Organizing Maps, 210-221, 2019
52019
Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction
JP Göpfert, C Göpfert, M Botsch, B Hammer
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017
52017
Convergence of multi-pass large margin nearest neighbor metric learning
C Göpfert, B Paassen, B Hammer
Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016
52016
How to compare adversarial robustness of classifiers from a global perspective
N Risse, C Göpfert, JP Göpfert
International Conference on Artificial Neural Networks, 29-41, 2021
42021
Analyzing Feature Relevance for Linear Reject Option SVM using Relevance Intervals
C Göpfert, JP Göpfert, B Hammer
Proceedings of the 2017 NIPS workshop on Transparent and Interpretable …, 2017
12017
Guiding Information: Supervised Models and their Relationship with Data
C Göpfert
2023
Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood
B Paaßen, C Göpfert, N Pinkwart
Proceedings of the 15th International Conference on Educational Data Mining …, 2022
2022
Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile
B Paaßen, C Göpfert, N Pinkwart
2022
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Artikkelit 1–20