Matthias Schonlau

26 papers A* 4B 3Journal 19
YearRankTypeTitle / Venue / Authors
2025 J jnl
The Hammock Plot: Where Categorical and Numerical Data Relax Together.
CoRR
Matthias Schonlau, Tiancheng Yang
2024 J jnl
Hammock Plots: Visualizing Categorical and Numerical Variables.
J. Comput. Graph. Stat.
Matthias Schonlau
2024 J jnl
exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies.
PeerJ Comput. Sci.
Tiancheng Yang, Ilia Sucholutsky, Kuang-Yu Jen, Matthias Schonlau
2023 J jnl
Multi-label classification of open-ended questions with BERT.
CoRR
Matthias Schonlau, Julia Weiß, Jan Marquardt
2021 A* conf
'Less Than One'-Shot Learning: Learning N Classes From M < N Samples.
AAAI
Ilia Sucholutsky, Matthias Schonlau
2021 B conf
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes.
IJCNN
Ilia Sucholutsky, Nam-Hwui Kim, Ryan P. Browne, Matthias Schonlau
2021 J jnl
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes.
CoRR
Ilia Sucholutsky, Nam-Hwui Kim, Ryan P. Browne, Matthias Schonlau
2021 J jnl
Optimal 1-NN prototypes for pathological geometries.
PeerJ Comput. Sci.
Ilia Sucholutsky, Matthias Schonlau
2021 A* conf
SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract).
AAAI
Ilia Sucholutsky, Matthias Schonlau
2021 B conf
Soft-Label Dataset Distillation and Text Dataset Distillation.
IJCNN
Ilia Sucholutsky, Matthias Schonlau
2020 J jnl
'Less Than One'-Shot Learning: Learning N Classes From M<N Samples.
CoRR
Ilia Sucholutsky, Matthias Schonlau
2020 J jnl
Optimal 1-NN Prototypes for Pathological Geometries.
CoRR
Ilia Sucholutsky, Matthias Schonlau
2020 J jnl
SecDD: Efficient and Secure Method for Remotely Training Neural Networks.
CoRR
Ilia Sucholutsky, Matthias Schonlau
2019 B conf
Deep Learning for System Trace Restoration.
IJCNN
Ilia Sucholutsky, Apurva Narayan, Matthias Schonlau, Sebastian Fischmeister
2019 J jnl
Deep Learning for System Trace Restoration.
CoRR
Ilia Sucholutsky, Apurva Narayan, Matthias Schonlau, Sebastian Fischmeister
2019 J jnl
Improving Dataset Distillation.
CoRR
Ilia Sucholutsky, Matthias Schonlau
2019 J jnl
Nearest labelset using double distances for multi-label classification.
PeerJ Comput. Sci.
Hyukjun Gweon, Matthias Schonlau, Stefan H. Steiner
2019 J jnl
Pay attention and you won't lose it: a deep learning approach to sequence imputation.
PeerJ Comput. Sci.
Ilia Sucholutsky, Apurva Narayan, Matthias Schonlau, Sebastian Fischmeister
2019 J jnl
The k conditional nearest neighbor algorithm for classification and class probability estimation.
PeerJ Comput. Sci.
Hyukjun Gweon, Matthias Schonlau, Stefan H. Steiner
2017 J jnl
Nearest Labelset Using Double Distances for Multi-label Classification.
CoRR
Hyukjun Gweon, Matthias Schonlau, Stefan H. Steiner
2016 J jnl
Using a Gaussian Process as a Nonparametric Regression Model.
Qual. Reliab. Eng. Int.
James R. Gattiker, Michael S. Hamada, David Higdon, Matthias Schonlau, William J. Welch
2004 J jnl
Visualizing non-hierarchical and hierarchical cluster analyses with clustergrams.
Comput. Stat.
Matthias Schonlau
2000 A* conf
Defection detection: using activity profiles to predict ISP customer vulnerability.
KDD
Nandini Raghavan, Robert M. Bell, Matthias Schonlau
2000 J jnl
Detecting masquerades in intrusion detection based on unpopular commands.
Inf. Process. Lett.
Matthias Schonlau, Martin Theus
1998 A* conf
A Fast Computer Intrusion Detection Algorithm Based on Hypothesis Testing of Command Transition Probabilities.
KDD
William DuMouchel, Matthias Schonlau
1998 J jnl
Efficient Global Optimization of Expensive Black-Box Functions.
J. Glob. Optim.
Donald R. Jones, Matthias Schonlau, William J. Welch