Sibylle Hess

27 papers A* 2A 1B 1Journal 15Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Spatially-Aware Multiple Instance Learning Framework for Digital Pathology.
CoRR
Hassan Keshvarikhojasteh, Mihail Tifrea, Sibylle Hess, Josien P. W. Pluim, Mitko Veta
2025 J jnl
How NOT to benchmark your SITE metric: Beyond Static Leaderboards and Towards Realistic Evaluation.
CoRR
Prabhant Singh, Sibylle Hess, Joaquin Vanschoren
2025 J jnl
Occam's model: Selecting simpler representations for better transferability estimation.
CoRR
Prabhant Singh, Sibylle Hess, Joaquin Vanschoren
2025 J jnl
SpaCE-VAE: Sparse and Confident Explanations usingVariational Autoencoders.
SIGKDD Explor.
Alexander Liu, Sibylle Hess
2024 — conf
Purifying Adversarial Examples Using an Autoencoder.
DS (2)
Thijs van Weezel, Famke van Ree, Tychon Bos, Patrick Bastiaanssen, Sibylle Hess
2024 J jnl
Scoring rule nets: beyond mean target prediction in multivariate regression.
CoRR
Daan Roordink, Sibylle Hess
2023 B ed.
Advances in Intelligent Data Analysis XXI - 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12-14, 2023, Proceedings
IDA
Bruno Crémilleux, Sibylle Hess, Siegfried Nijssen
2023 — conf
Scoring Rule Nets: Beyond Mean Target Prediction in Multivariate Regression.
ECML/PKDD (2)
Daan Roordink, Sibylle Hess
2022 — ch.
Matrix Factorization with Binary Constraints.
Mach. Learn. under Resour. Constraints Vol. 1 (1)
Sibylle Hess
2022 A* conf
Shrub Ensembles for Online Classification.
AAAI
Sebastian Buschjäger, Sibylle Hess, Katharina Morik
2021 J jnl
BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent.
Data Min. Knowl. Discov.
Sibylle Hess, Gianvito Pio, Michiel E. Hochstenbach, Michelangelo Ceci
2021 J jnl
Shrub Ensembles for Online Classification.
CoRR
Sebastian Buschjäger, Sibylle Hess, Katharina Morik
2020 J jnl
How to cheat the page limit.
WIREs Data Mining Knowl. Discov.
Wouter Duivesteijn, Sibylle Hess, Xin Du
2020 J jnl
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring.
CoRR
Sibylle Hess, Wouter Duivesteijn, Decebal Constantin Mocanu
2019 J jnl
C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization.
CoRR
Sibylle Hess, Katharina Morik
2019 J jnl
The PRIMPing Routine - Tiling through Proximal Alternating Linearized Minimization.
CoRR
Sibylle Hess, Katharina Morik, Nico Piatkowski
2019 A* conf
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.
AAAI
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik
2019 J jnl
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.
CoRR
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik
2019 J jnl
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization.
CoRR
Sibylle Hess, Nico Piatkowski, Katharina Morik
2019 — conf
k Is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities.
ECML/PKDD (1)
Sibylle Hess, Wouter Duivesteijn
2019 J jnl
k is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities.
CoRR
Sibylle Hess, Wouter Duivesteijn
2018 — —
A mathematical theory of making hard decisions: model selection and robustness of matrix factorization with binary constraints
Sibylle Hess
2018 — conf
The Relationship of DBSCAN to Matrix Factorization and Spectral Clustering.
LWDA
Erich Schubert, Sibylle Hess, Katharina Morik
2018 A conf
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization.
SDM
Sibylle Hess, Nico Piatkowski, Katharina Morik
2017 — conf
C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization.
ECML/PKDD (1)
Sibylle Hess, Katharina Morik
2017 J jnl
The PRIMPING routine - Tiling through proximal alternating linearized minimization.
Data Min. Knowl. Discov.
Sibylle Hess, Katharina Morik, Nico Piatkowski
2014 — conf
SHrimp: Descriptive Patterns in a Tree.
LWA
Sibylle Hess, Nico Piatkowski, Katharina Morik