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Anzahl der Publikationen: 73

Zeitschriftenartikel

Scholbeck, Christian A. ORCID logoORCID: https://orcid.org/0000-0001-6607-4895; Casalicchio, Giuseppe ORCID logoORCID: https://orcid.org/0000-0001-5324-5966; Molnar, Christoph; Bischl, Bernd und Heumann, Christian (2024): Marginal effects for non-linear prediction functions. In: Data Mining and Knowledge Discovery, Bd. 38, Nr. 5: S. 2997-3042 [PDF, 10MB]

Schalk, Daniel; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202 (2024): Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models. In: Statistics and Computing, Bd. 34, Nr. 1, 31 [PDF, 835kB]

Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202; Pfisterer, Florian; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Grün, Bettina (2023): Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods. In: AStA Advances in Statistical Analysis [Forthcoming]

Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980; Binder, Martin; Lang, Michel ORCID logoORCID: https://orcid.org/0000-0001-9754-0393; Pielok, Tobias; Richter, Jakob ORCID logoORCID: https://orcid.org/0000-0003-4481-5554; Coors, Stefan ORCID logoORCID: https://orcid.org/0000-0002-7465-2146; Thomas, Janek; Ullmann, Theresa ORCID logoORCID: https://orcid.org/0000-0003-1215-8561; Becker, Marc ORCID logoORCID: https://orcid.org/0000-0002-8115-0400; Boulesteix, Anne‐Laure ORCID logoORCID: https://orcid.org/0000-0002-2729-0947; Deng, Difan und Lindauer, Marius ORCID logoORCID: 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]

Rath, Katharina ORCID logoORCID: https://orcid.org/0000-0002-4962-5656; Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980; Toussaint, Udo von; Rea, Cristina ORCID logoORCID: https://orcid.org/0000-0002-9948-2649; Maris, Andrew; Granetz, Robert und Albert, Christopher G. ORCID logoORCID: 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]

Pargent, Florian ORCID logoORCID: https://orcid.org/0000-0002-2388-553X; Pfisterer, Florian; Thomas, Janek und Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 (2022): Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. In: Computational Statistics, Bd. 37, Nr. 5: S. 2671-2692 [PDF, 697kB]

Au, Quay; Herbinger, Julia; Stachl, Clemens; Bischl, Bernd und Casalicchio, Giuseppe (2022): Grouped feature importance and combined features effect plot. In: Data Mining and Knowledge Discovery, Bd. 36, Nr. 4: S. 1401-1450

Schalk, Daniel; Bischl, Bernd und Ruegamer, David (2022): Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization. In: Journal of Computational and Graphical Statistics, Bd. 32, Nr. 2: S. 631-641

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

Ott, Felix; Rügamer, David; Heublein, Lucas; Hamann, Tim; Barth, Jens; Bischl, Bernd und Mutschler, Christopher (2022): Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens. In: International Journal on Document Analysis and Recognition, Bd. 25, Nr. 4: S. 385-414

Stachl, Clemens ORCID logoORCID: https://orcid.org/0000-0002-4498-3067; Au, Quay ORCID logoORCID: https://orcid.org/0000-0002-5252-8902; Schoedel, Ramona; Gosling, Samuel D. ORCID logoORCID: https://orcid.org/0000-0001-8970-591X; Harari, Gabriella M.; Buschek, Daniel ORCID logoORCID: https://orcid.org/0000-0002-0013-715X; Voelkel, Sarah Theres; Schuwerk, Tobias ORCID logoORCID: https://orcid.org/0000-0003-3720-7120; Oldemeier, Michelle; Ullmann, Theresa ORCID logoORCID: https://orcid.org/0000-0003-1215-8561; Hussmann, Heinrich; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Bühner, Markus ORCID logoORCID: 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

Sonabend, Raphael; Kiraly, Franz J.; Bender, Andreas; Bischl, Bernd und Lang, Michel (2021): mlr3proba: an R package for machine learning in survival analysis. In: Bioinformatics, Bd. 37, Nr. 17: S. 2789-2791

Schratz, Patrick; Muenchow, Jannes; Iturritxa, Eugenia; Cortes, Jose; Bischl, Bernd und Brenning, Alexander (2021): Monitoring Forest Health Using Hyperspectral Imagery: Does Feature Selection Improve the Performance of Machine-Learning Techniques? In: Remote Sensing, Bd. 13, Nr. 23, 4832

Rath, Katharina; Albert, Christopher G.; Bischl, Bernd und Toussaint, Udo von (2021): Symplectic Gaussian process regression of maps in Hamiltonian systems. In: Chaos, Bd. 31, Nr. 5, 53121

Binder, Martin; Pfisterer, Florian; Lang, Michel; Schneider, Lennart; Kotthoff, Lars und Bischl, Bernd (2021): mlr3pipelines-Flexible Machine Learning Pipelines in R. In: Journal of Machine Learning Research, Bd. 22

Binder, Martin; Moosbauer, Julia; Thomas, Janek und Bischl, Bernd (2020): Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles. In: Gecco'20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference: S. 471-479

Sun, Xudong; Bommert, Andrea; Pfisterer, Florian; Rähenfürher, Jörg; Lang, Michel und Bischl, Bernd (2020): High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions. In: Intelligent Systems and Applications, Vol 1, Bd. 1037: S. 629-647

Bommert, Andrea; Sun, Xudong; Bischl, Bernd; Rahnenfuehrer, Jörg und Lang, Michel (2020): Benchmark for filter methods for feature selection in high-dimensional classification data. In: Computational Statistics & Data Analysis, Bd. 143, 106839

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]

Ellenbach, Nicole; Boulesteix, Anne-Laure; Bischl, Bernd; Unger, Kristian und Hornung, Roman (2020): Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning. In: Journal of Classification, Bd. 38: S. 212-231 [PDF, 709kB]

Probst, Philipp; Boulesteix, Anne-Laure und Bischl, Bernd (2019): Tunability: Importance of Hyperparameters of Machine Learning Algorithms. In: Journal of Machine Learning Research, Bd. 20, 53

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

Beggel, Laura; Kausler, Bernhard X.; Schiegg, Martin; Pfeiffer, Michael und Bischl, Bernd (2019): Time series anomaly detection based on shapelet learning. In: Computational Statistics, Bd. 34, Nr. 3: S. 945-976

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

Thomas, Janek; Mayr, Andreas; Bischl, Bernd; Schmid, Matthias; Smith, Adam und Hofner, Benjamin (2018): Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates. In: Statistics and Computing, Bd. 28, Nr. 3: S. 673-687

Goerigk, Stephan; Hilbert, Sven; Jobst, Andrea; Falkai, Peter ORCID logoORCID: 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

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

Probst, Philipp; Au, Quay; Casalicchio, Giuseppe; Stachl, Clemens und Bischl, Bernd (2017): Multilabel Classification with R Package mlr. In: R Journal, Bd. 9, Nr. 1: S. 352-369

Probst, Philipp; Au, Quay; Casalicchio, Giuseppe; Stachl, Clemens und Bischl, Bernd (2017): Multilabel Classification with R Package mlr. In: The R Journal

Thomas, Janek; Hepp, Tobias; Mayr, Andreas und Bischl, Bernd (2017): Probing for Sparse and Fast Variable Selection with Model-Based Boosting. In: Computational and Mathematical Methods in Medicine, Bd. 2017, 1421409 [PDF, 1MB]

Feilke, Martina; Bischl, Bernd; Schmid, Volker J. ORCID logoORCID: https://orcid.org/0000-0003-2195-8130 und Gertheiss, Jan (2016): Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data. In: Methods of Information in Medicine, Bd. 55, Nr. 1: S. 31-41

Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure und Schmid, Matthias (2016): The residual-based predictiveness curve: A visual tool to assess the performance of prediction models. In: Biometrics, Bd. 72, Nr. 2: S. 392-401

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

Horn, Daniel; Demircioğlu, Aydin; Bischl, Bernd; Glasmachers, Tobias und Weihs, Claus (2016): A Comparative Study on Large Scale Kernelized Support Vector Machines. In: Advances in Data Analysis and Classification: S. 1-17

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

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; 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

Bischl, Bernd; Lang, Michel; Mersmann, Olaf; Rahnenführer, Jörg und Weihs, Claus (2015): BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments. In: Journal of Statistical Software, Bd. 64, Nr. 11: S. 1-25

Kotthaus, Helena; Korb, Ingo; Lang, Michel; Bischl, Bernd; Rahnenführer, Jörg und Marwedel, Peter (2015): Runtime and memory consumption analyses for machine learning R programs. In: Journal of Statistical Computation and Simulation, Bd. 85, Nr. 1: S. 14-29

Lang, Michel; Kotthaus, Helena; Marwedel, Peter; Weihs, Claus; Rahnenführer, Jörg und Bischl, Bernd (2015): Automatic model selection for high-dimensional survival analysis. In: Journal of Statistical Computation and Simulation, Bd. 85, Nr. 1: S. 62-76

Paper

Schüller, Nicole; Boulesteix, Anne-Laure; Bischl, Bernd; Unger, Kristian und Hornung, Roman (18. März 2019): Improved outcome prediction across data sources through robust parameter tuning. Department of Statistics: Technical Reports, Nr. 221 [PDF, 522kB]

Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure und Schmid, Matthias (9. Januar 2015): The Residual-based Predictiveness Curve - A Visual Tool to Assess the Performance of Prediction Models. Department of Statistics: Technical Reports, Nr. 178 [PDF, 1MB]

Buchbeitrag

Bender, Andreas ORCID logoORCID: https://orcid.org/0000-0001-5628-8611; Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202; Scheipl, Fabian ORCID logoORCID: https://orcid.org/0000-0001-8172-3603 und Bischl, Bernd ORCID logoORCID: 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

Bischl, Bernd; Kühn, Tobias und Szepannek, Gero (2016): On Class Imbalance Correction for Classification Algorithms in Credit Scoring. In: Lübbecke, Marco (Hrsg.): Operations Research Proceedings 2014. Cham: Springer International Publishing. S. 37-43

Bauer, Nadja; Friedrichs, Klaus; Bischl, Bernd und Weihs, Claus (2016): Fast Model Based Optimization of Tone Onset Detection by Instance Sampling. In: Wilhelm, Adalbert F. X. und Kestler, Hans A. (Hrsg.): Analysis of Large and Complex Data. Cham: Springer. S. 461-472

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

Weihs, Claus; Horn, Daniel und Bischl, Bernd (2016): Big data Classification: Aspects on Many Features and Many Observations. In: Wilhelm, Adalbert F.X. und Kestler, Hans A. (Hrsg.): Analysis of Large and Complex Data. Cham ; Heidelberg ; New York ; Dordrecht ; London: Springer. S. 113-122

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

Konferenzbeitrag

Vahidi, Amihossein; Wimmer, Lisa; Gündüz, Hüseyin Anil; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Rezaei, Mina (September 2024): Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), Vilnius, Lithuania, 9. - 13. September 2024. In: Machine Learning and Knowledge Discovery in Databases Part I, LNCS Bd. 14941 Springer Cham. S. 38-55 [PDF, 904kB]

Herrmann, Moritz ORCID logoORCID: https://orcid.org/0000-0002-4893-5812; Lange, F. Julian D.; Eggensperger, Katharina; Casalicchio, Giuseppe; Wever, Marcel ORCID logoORCID: https://orcid.org/0000-0001-9782-6818; Feurer, Matthias; Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108; Boulesteix, Anne-Laure und Bischl, Bernd (Juli 2024): Position: Why We Must Rethink Empirical Research in Machine Learning. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 21. - 27. July 2024. In: Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research Bd. 235 PMLR. S. 18228-18247 [PDF, 334kB]

Vahidi, Amirhossein; Schosser, Simon; Wimmer, Lisa; Li, Yawei; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Rezaei, Mina (Mai 2024): Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, 7. - 11. May 2024. [PDF, 439kB]

Wimmer, Lisa; Sale, Yusuf; Hofman, Paul; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke ORCID logoORCID: 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 [PDF, 1MB]

Dandl, Susanne ORCID logoORCID: https://orcid.org/0000-0003-4324-4163; Casalicchio, Giuseppe ORCID logoORCID: https://orcid.org/0000-0001-5324-5966; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Bothmann, Ludwig ORCID logoORCID: https://orcid.org/0000-0002-1471-6582 (2023): Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. ECML PKDD 2023, Torino, Italy, September 18 -22 2023. Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis, Elena und Bonchi, Francesco (Hrsg.): In: Machine Learning and Knowledge Discovery in Databases : Research Track : European conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023 : proceedings, Bd. 14171 Cham: Springer. S. 479-495

Schneider, Lennart ORCID logoORCID: https://orcid.org/0000-0003-4152-5308; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Thomas, Janek ORCID logoORCID: https://orcid.org/0000-0003-4511-6245 (2023): Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models. GECCO '23: Genetic and Evolutionary Computation Conference, Lisbon Portugal, July 15 - 19, 2023. Silva, Sara und Paquete, Luís (Hrsg.): In: GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference, New York, NY, United States: Association for Computing Machinery. S. 538-547 [PDF, 781kB]

Rauch, Lukas; Aßenmacher, Matthias ORCID logoORCID: https://orcid.org/0000-0003-2154-5774; Huseljic, Denis; Wirth, Moritz; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Sick, Bernhard (2023): ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023. Koutra, Danai ORCID logoORCID: https://orcid.org/0000-0002-3206-8179; Plant, Claudia ORCID logoORCID: https://orcid.org/0000-0001-5274-8123; Gomez Rodriguez, Manuel ORCID logoORCID: https://orcid.org/0000-0003-3930-1161; Baralis, Elena ORCID logoORCID: https://orcid.org/0000-0001-9231-467X und Bonchi, Francesco ORCID logoORCID: https://orcid.org/0000-0001-9464-8315 (Hrsg.): In: Machine Learning and Knowledge Discovery in Databases: Research Track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part I, Bd. 14169 Cham: Springer. S. 55-74

Segel, Sarah ORCID logoORCID: https://orcid.org/0009-0005-2966-266X; Graf, Helena ORCID logoORCID: https://orcid.org/0000-0001-9447-0609; Tornede, Alexander ORCID logoORCID: https://orcid.org/0000-0002-2415-2186; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Lindauer, Marius ORCID logoORCID: https://orcid.org/0000-0002-9675-3175 (2023): Symbolic Explanations for Hyperparameter Optimization. International Conference on Automated Machine Learning, Potsdam, Germany, 12-15 November 2023. Faust, Aleksandra; Garnett, Roman; White, Colin; Hutter, Frank und Gardner, Jacob R. (Hrsg.): In: Proceedings of Machine Learning Research, Bd. 224 Cambridge, MA: JMLR. [PDF, 12MB]

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]

Rezaei, Mina; Dorigatti, Emilio; Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202 und Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 (2022): Joint Debiased Representation Learning and Imbalanced Data Clustering. 2022 IEEE International Conference on Data Mining Workshops (ICDMW), Orlando, Florida, 28 November–1 December 2022. In: 2022 IEEE International Conference on Data Mining Workshops (ICDMW), Los Alamitos: IEEE. S. 55-62

Weber, Tobias ORCID logoORCID: https://orcid.org/0000-0002-5430-2595; Ingrisch, Michael ORCID logoORCID: https://orcid.org/0000-0003-0268-9078; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Rügamer, David ORCID logoORCID: 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]

Dandl, Susanne; Pfisterer, Florian und Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 (2022): Multi-objective counterfactual fairness. GECCO '22, Genetic and Evolutionary Computation Conference, Boston Massachusetts, July 9 - 13, 2022. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, New York: Association for Computing Machinery. S. 328-331

Schneider, Lennart; Pfisterer, Florian; Thomas, Janek und Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 (2022): A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. GECCO '22: Genetic and Evolutionary Computation Conference, Boston Massachusetts (hybrid), July 9-13, 2022. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association of Computing Machinery: New York. S. 2136-2142

Schneider, Lennart ORCID logoORCID: https://orcid.org/0000-0003-4152-5308; Schäpermeier, Lennart ORCID logoORCID: https://orcid.org/0000-0003-3929-7465; Prager, Raphael Patrick ORCID logoORCID: https://orcid.org/0000-0003-1237-4248; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980; Trautmann, Heike ORCID logoORCID: https://orcid.org/0000-0002-9788-8282 und Kerschke, Pascal ORCID logoORCID: 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 logoORCID: 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

Kopper, Philipp; Wiegrebe, Simon; Bischl, Bernd; Bender, Andreas ORCID logoORCID: https://orcid.org/0000-0001-5628-8611 und Rügamer, David ORCID logoORCID: 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

Ott, Felix; Rügamer, David ORCID logoORCID: https://orcid.org/0000-0002-8772-9202; Heublein, Lucas; Bischl, Bernd ORCID logoORCID: 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 logoORCID: 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 logoORCID: 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

Herbinger, Julia; Bischl, Bernd ORCID logoORCID: https://orcid.org/0000-0001-6002-6980 und Casalicchio, Giuseppe (2022): REPID: Regional Effect Plots with implicit Interaction Detection. International Conference on Artificial Intelligence and Statistics, Online, 28-30 March 2022. Camps-Valls, Gustau; Ruiz, Francisco J. R. und Valera, Isabel (Hrsg.): In: Proceedings of The 25th International Conference on Artificial Intelligence and Statistics, Bd. 151

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

Goschenhofer, Jann; Hvingelby, Rasmus; Rügamer, David ORCID logoORCID: 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

Degroote, Hans; Bischl, Bernd; Kotthoff, Lars und De Causmaecker, Patrick (2016): Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study. 16th ITAT Conference Information Technologies - Applications and Theory, Tatranské Matliare, 15.-19. September 2016. In: Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory, S. 93-101

Horn, Daniel und Bischl, Bernd (2016): Multi-Objective Parameter Configuration of Machine Learning Algorithms using Model-Based Optimization. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece, 6-9 December 2016. IEEE Computer Society.

Brockhoff, Dimo; Bischl, Bernd und Wagner, Tobias (2015): The Impact of Initial Designs on the Performance of MATSuMoTo on the Noiseless BBOB-2015 Testbed: A Preliminary Study. Genetic and Evolutionary Computation Conference 2015, Madrid, 11.-15. Juli 2015. In: GECCO '15 Companion, Madrid:

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