Anzahl der Publikationen: 65
2024
2023
Wimmer, Lisa; Sale, Yusuf; Hofman, Paul; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke
ORCID: https://orcid.org/0000-0002-9944-4108
(2023):
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 2282-2292
Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Binder, Martin; Lang, Michel
ORCID: https://orcid.org/0000-0001-9754-0393; Pielok, Tobias; Richter, Jakob
ORCID: https://orcid.org/0000-0003-4481-5554; Coors, Stefan
ORCID: https://orcid.org/0000-0002-7465-2146; Thomas, Janek; Ullmann, Theresa
ORCID: https://orcid.org/0000-0003-1215-8561; Becker, Marc
ORCID: https://orcid.org/0000-0002-8115-0400; Boulesteix, Anne‐Laure
ORCID: https://orcid.org/0000-0002-2729-0947; Deng, Difan und Lindauer, Marius
ORCID: https://orcid.org/0000-0002-9675-3175
(2023):
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.
In: WIREs Data Mining and Knowledge Discovery, Bd. 13, Nr. 2
[PDF, 6MB]
2022
Goschenhofer, Jann; Ragupathy, Pranav; Heumann, Christian; Bischl, Bernd und Aßenmacher, Matthias
(Dezember 2022):
CC-Top: Constrained Clustering for Dynamic Topic Discovery.
Proceedings of the The First Workshop on Ever Evolving NLP (EvoNLP), Abu Dhabi, UAE, 7.12.22 - 11.12.22.
S. 26-34
[PDF, 1MB]
Rath, Katharina
ORCID: https://orcid.org/0000-0002-4962-5656; Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Toussaint, Udo von; Rea, Cristina
ORCID: https://orcid.org/0000-0002-9948-2649; Maris, Andrew; Granetz, Robert und Albert, Christopher G.
ORCID: https://orcid.org/0000-0003-4773-416X
(2022):
Data augmentation for disruption prediction via robust surrogate models.
In: Journal of Plasma Physics, Bd. 88, Nr. 5: S. 1-23
[PDF, 1MB]
Weber, Tobias
ORCID: https://orcid.org/0000-0002-5430-2595; Ingrisch, Michael
ORCID: https://orcid.org/0000-0003-0268-9078; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980 und Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202
(2022):
Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs.
MICCAI Workshop on Medical Applications with Disentanglements, Singapore, 18. - 22. September 2022.
Fragemann, Jana; Li, Jianning; Liu, Xiao und Tsaftar, Sotirios A. (Hrsg.):
In: Medical Applications with Disentanglements,
Cham: Springer. S. 22-32
[PDF, 9MB]
Schneider, Lennart
ORCID: https://orcid.org/0000-0003-4152-5308; Schäpermeier, Lennart
ORCID: https://orcid.org/0000-0003-3929-7465; Prager, Raphael Patrick
ORCID: https://orcid.org/0000-0003-1237-4248; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Trautmann, Heike
ORCID: https://orcid.org/0000-0002-9788-8282 und Kerschke, Pascal
ORCID: https://orcid.org/0000-0003-2862-1418
(2022):
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
PPSN XVII. 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022.
In: Parallel Problem Solving from Nature – PPSN XVII. 17th International Conference, PPSN 2022, Dortmund, Germany, September 10–14, 2022, Proceedings, Part I, Lecture Notes in Computer Science
Bd. 13398
Cham, Switzerland: Springer. S. 575-589
Soleymani, Farzin; Eslami, Mohammad; Elze, Tobias; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Rezaei, Mina; Išgum, Ivana und Colliot, Olivier
(2022):
Deep variational clustering framework for self-labeling large-scale medical images.
Medical Imaging 2022: Image Processing, San Diego, California, United States, Online, 20–24 February 2022, 21-27 March 2022.
Colliot, Olivier; Išgum, Ivana; Landman, Bennett A. und Loew, Murray H. (Hrsg.):
In: Medical Imaging 2022: Image Processing : 20-24 February 2022, San Diego, California, United States : 21-27 March 2022, online, Proceedings of SPIE
Bd. 12032
Bellingham, Washington, USA: SPIE. S. 9
Ott, Felix; Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202; Heublein, Lucas; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980 und Mutschler, Christopher
(2022):
Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach.
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, 4-8 January 2022.
In: 2022 IEEE Winter Conference on Applications of Computer Vision : 4-8 January 2022, Waikoloa, Hawaii : proceedings,
Piscataway, NJ: IEEE. S. 1244-1254
Rezaei, Mina; Nappi, Janne; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Yoshida, Hiro; Iftekharuddin, Khan M.; Drukker, Karen; Mazurowski, Maciej A.; Lu, Hongbing; Muramatsu, Chisako und Samala, Ravi K.
(2022):
Bayesian uncertainty estimation for detection of long-tail and unseen conditions in abdominal images.
SPIE Medical Imaging, San Diego, California, United States, Online, 20-24 February 2022.
Deserno, Thomas M. und Park, Brian J. (Hrsg.):
In: Medical Imaging 2022: Computer-Aided Diagnosis,
Bellingham, Washington, USA: SPIE. S. 43
Rezaei, Mina; Näppi, Janne J.; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980; Yoshida, Hiro; Park, Brian J. und Deserno, Thomas M.
(2022):
Deep mutual GANs: representation learning from multiple experts.
SPIE Medical Imaging, 20–24 February 2022, San Diego, California, United States.
Deserno, Thomas M. und Park, Brian J. (Hrsg.):
In: Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications, SPIE Proceedings volume
Bd. 12037
Bellingham, Washington, USA: SPIE. S. 32
Moosbauer, Julia; Binder, Martin; Schneider, Lennart; Pfisterer, Florian; Becker, Marc; Lang, Michel; Kotthoff, Lars und Bischl, Bernd
(2022):
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers.
In: IEEE Transactions on Evolutionary Computation (T-Evc), Bd. 26, Nr. 6: S. 1336-1350
Kopper, Philipp; Wiegrebe, Simon; Bischl, Bernd; Bender, Andreas
ORCID: https://orcid.org/0000-0001-5628-8611 und Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202
(2022):
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.
26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2022), Chengdu, China, May 16–19, 2022.
Gama, João (Hrsg.):
In: Advances in Knowledge Discovery and Data Mining. 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part II, Lecture Notes in Computer Science
Bd. 13281
Cham: Springer. S. 249-261
2021
Goschenhofer, Jann; Hvingelby, Rasmus; Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202; Thomas, Janek; Wagner, Moritz und Bischl, Bernd
(2021):
Deep Semi-supervised Learning for Time Series Classification.
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, CA, USA, 13-16 December 2021.
In: 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA),
New York: IEEE. S. 422-428
König, Gunnar; Molnar, Christoph; Bischl, Bernd und Grosse-Wentrup, Moritz
(2021):
Relative Feature Importance.
2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, 10-15 January 2021.
In: 2020 25th International Conference on Pattern Recognition (ICPR),
New York: IEEE. S. 9318-9325
Bender, Andreas
ORCID: https://orcid.org/0000-0001-5628-8611; Rügamer, David
ORCID: https://orcid.org/0000-0002-8772-9202; Scheipl, Fabian
ORCID: https://orcid.org/0000-0001-8172-3603 und Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980
(2021):
A General Machine Learning Framework for Survival Analysis.
In: Hutter, Frank; Kersting, Kristian; Lijffijt, Jefrey und Valera, Isabel (Hrsg.):
Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part III. Lecture Notes in Computer Science (LNCS), Bd. 12459. Cham: Springer. S. 158-173
Stachl, Clemens
ORCID: https://orcid.org/0000-0002-4498-3067; Au, Quay
ORCID: https://orcid.org/0000-0002-5252-8902; Schoedel, Ramona; Gosling, Samuel D.
ORCID: https://orcid.org/0000-0001-8970-591X; Harari, Gabriella M.; Buschek, Daniel
ORCID: https://orcid.org/0000-0002-0013-715X; Voelkel, Sarah Theres; Schuwerk, Tobias
ORCID: https://orcid.org/0000-0003-3720-7120; Oldemeier, Michelle; Ullmann, Theresa
ORCID: https://orcid.org/0000-0003-1215-8561; Hussmann, Heinrich; Bischl, Bernd
ORCID: https://orcid.org/0000-0001-6002-6980 und Bühner, Markus
ORCID: https://orcid.org/0000-0002-0597-8708
(2021):
Predicting personality from patterns of behavior collected with smartphones.
In: Proceedings of the National Academy of Sciences of the United States of America, Bd. 118, Nr. 29, 1920484117
2020
Pfister, Franz M. J.; Um, Terry Taewoong; Pichler, Daniel C.; Goschenhofer, Jann; Abedinpour, Kian; Lang, Muriel; Endo, Satoshi; Ceballos-Baumann, Andres O.; Hirche, Sandra; Bischl, Bernd; Kulic, Dana und Fietzek, Urban M.
(2020):
High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.
In: Scientific Reports, Bd. 10, Nr. 1, 5860
[PDF, 2MB]
2019
Casalicchio, Giuseppe; Bossek, Jakob; Lang, Michel; Kirchhoff, Dominik; Kerschke, Pascal; Hofner, Benjamin; Seibold, Heidi; Vanschoren, Joaquin und Bischl, Bernd
(2019):
OpenML: An R package to connect to the machine learning platform OpenML.
In: Computational Statistics, Bd. 34, Nr. 3: S. 977-991
2018
Schödel, Ramona; Au, Quay; Völkel, Sarah Theres; Lehmann, Florian; Becker, Daniela; Bühner, Markus; Bischl, Bernd; Hussmann, Heinrich und Stachl, Clemens
(2018):
Digital Footprints of Sensation Seeking. A Traditional Concept in the Big Data Era.
In: Zeitschrift für Psychologie-Journal of Psychology, Bd. 226, Nr. 4: S. 232-245
Goerigk, Stephan; Hilbert, Sven; Jobst, Andrea; Falkai, Peter
ORCID: https://orcid.org/0000-0003-2873-8667; Bühner, Markus; Stachl, Clemens; Bischl, Bernd; Coors, Stefan; Ehring, Thomas; Padberg, Frank und Sarubin, Nina
(2018):
Predicting instructed simulation and dissimulation when screening for depressive symptoms.
In: European Archives of Psychiatry and Clinical Neuroscience, Bd. 268, Nr. 1: S. 1-16
2017
Stachl, Clemens; Hilbert, Sven; Au, Jiew-Quay; Buschek, Daniel; Luca, Alexander De; Bischl, Bernd; Hussmann, Heinrich und Bühner, Markus
(2. August 2017):
Personality Traits Predict Smartphone Usage.
In: European Journal of Personality, Bd. 31, Nr. 6: S. 701-722
2016
Schiffner, Julia; Bischl, Bernd; Lang, Michel; Richter, Jakob; Jones, Zachary M.; Probst, Philipp; Pfisterer, Florian; Gallo, Mason; Kirchhoff, Dominik; Kühn, Tobias; Thomas, Janek und Kotthoff, Lars
(2016):
mlr Tutorial.
In: CoRR, Bd. abs/1609.06146
Bischl, Bernd; Kerschke, Pascal; Kotthoff, Lars; Lindauer, Marius; Malitsky, Yuri; Frechétte, Alexandre; Hoos, Holger; Hutter, Frank; Leyton-Brown, Kevin; Tierney, Kevin und Vanschoren, Joaquin
(2016):
ASlib: A Benchmark Library for Algorithm Selection.
In: Artificial Intelligence, Bd. 237: S. 41-58
Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe und Jones, Zachary M.
(2016):
mlr: Machine Learning in R.
In: Journal of Machine Learning Research, Bd. 17, Nr. 1: S. 5938-5942
Richter, Jakob; Kotthaus, Helena; Bischl, Bernd; Marwedel, Peter; Rahnenführer, Jörg und Lang, Michel
(2016):
Faster Model-Based Optimization Through Resource-Aware Scheduling Strategies.
In:
Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 - June 1, 2016, Revised Selected Papers. Theoretical Computer Science and General Issues, Bd. 10079. Cham: Springer. S. 267-273
Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jajob; Studerus, Erich; Casalicchio, Giuseppe und Jones, Zachary M.
(2016):
mlr: Machine Learning in R.
In: Journal of Machine Learning Research, Bd. 17, 1
2015
Horn, Daniel; Wagner, Tobias; Biermann, Dirk; Weihs, Claus und Bischl, Bernd
(2015):
Model-Based Multi-Objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark.
In: Gaspar-Cunha, António; Henggeler Antunes, Carlos und Coello, Carlos Coello (Hrsg.):
Evolutionary Multi-Criterion Optimization (EMO). 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 - April 1, 2015. Proceedings, Part I. Lecture Notes in Computer Science, Bd. 9018. Berlin: Springer. S. 64-78
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