Publications

Christina Göpfert, Yinlam Chow, Chih-wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier (2022). Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. The Web Conference.

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Niklas Risse, Christina Göpfert, Jan Philip Göpfert (2021). How to compare adversarial robustness of classifiers from a global perspective. International Conference on Artificial Neural Networks (ICANN).

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Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin, Ruth Urner (2019). When can unlabeled data improve the learning rate?. Conference on Learning Theory.

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Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer (2019). FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CoRR.

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Johannes Brinkrolf, Christina Göpfert, Barbara Hammer (2019). Differential privacy for learning vector quantization. Neurocomputing.

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Christina Göpfert, Lukas Pfannschmidt, Jan Philip Göpfert, Barbara Hammer (2018). Interpretation of linear classifiers by means of feature relevance bounds. Neurocomputing.

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Benjamin Paaßen, Christina Göpfert, Barbara Hammer (2017). Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Processing Letters.

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Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer (2017). Feature Relevance Bounds for Linear Classification. Proceedings of the ESANN.

Jan Philip Göpfert, Christina Göpfert, Mario Botsch, Barbara Hammer (2017). Effects of Variability in Synthetic Training Data on Convolutional Neural Networks for 3D Head Reconstruction. Proceedings of IEEE Symposium Series on Computational Intelligence.

Christina Göpfert, Jan Philip Göpfert, Barbara Hammer (2017). Analyzing Feature Relevance for Linear Reject Option SVM using Relevance Intervals. Proceedings of the 2017 NIPS workshop on Transparent and Interpretable Machine Learning in Safety Critical Environments.

Benjamin Paaßen, Christina Göpfert, Barbara Hammer (2016). Gaussian process prediction for time series of structured data. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.

Johannes Kummert, Benjamin Paaßen, Joris Jensen, Christina Göpfert, Barbara Hammer (2016). Local Reject Option for Deterministic Multi-class SVM. Artificial Neural Networks and Machine Learning - ICANN 2016 - 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II.

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Christina Göpfert, Benjamin Paaßen, Barbara Hammer (2016). Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part 1.

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