Bernd Bischl
Orcid: 0000-0001-6002-6980Affiliations:
- LMU Munich, Department of Statistics, Germany
According to our database1,
Bernd Bischl
authored at least 200 papers
between 2009 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on d-nb.info
On csauthors.net:
Bibliography
2024
Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models.
Stat. Comput., February, 2024
J. Artif. Intell. Res., 2024
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration.
CoRR, 2024
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
CoRR, 2024
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
ACM Trans. Evol. Learn. Optim., December, 2023
Comput. Vis. Image Underst., October, 2023
Big Data, June, 2023
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization.
J. Comput. Graph. Stat., April, 2023
J. Open Source Softw., March, 2023
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.
WIREs Data. Mining. Knowl. Discov., 2023
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
J. Stat. Softw., 2023
CoRR, 2023
Evaluating machine learning models in non-standard settings: An overview and new findings.
CoRR, 2023
CoRR, 2023
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning.
CoRR, 2023
Smoothing the Edges: A General Framework for Smooth Optimization in Sparse Regularization using Hadamard Overparametrization.
CoRR, 2023
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments.
CoRR, 2023
Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition.
IEEE Access, 2023
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
Proceedings of the Explainable Artificial Intelligence, 2023
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023
Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences.
Proceedings of the International Conference on Machine Learning and Applications, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering.
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), 2023
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features.
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2023
Proceedings of the International Conference on Automated Machine Learning, 2023
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML.
Proceedings of the International Conference on Automated Machine Learning, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
IEEE Trans. Evol. Comput., 2022
Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens.
Int. J. Document Anal. Recognit., 2022
Data Min. Knowl. Discov., 2022
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features.
Comput. Stat., 2022
CoRR, 2022
CoRR, 2022
CoRR, 2022
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression.
CoRR, 2022
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
CoRR, 2022
Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution.
CoRR, 2022
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022
HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022
Bayesian uncertainty estimation for detection of long-tail and unseen conditions in abdominal images.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
Uncertainty-aware Evaluation of Time-series Classification for Online Handwriting Recognition with Domain Shift.
Proceedings of the 1st International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2022) co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI 2022, 2022
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition.
Proceedings of the Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges, 2022
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the International Conference on Automated Machine Learning, 2022
YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Monitoring Forest Health Using Hyperspectral Imagery: Does Feature Selection Improve the Performance of Machine-Learning Techniques?
Remote. Sens., 2021
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation.
CoRR, 2021
CoRR, 2021
CoRR, 2021
YAHPO Gym - Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization.
CoRR, 2021
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
CoRR, 2021
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT).
CoRR, 2021
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.
CoRR, 2021
J. Classif., 2021
IEEE Access, 2021
Proceedings of AAAI Symposium on Survival Prediction, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
2020
Benchmark for filter methods for feature selection in high-dimensional classification data.
Comput. Stat. Data Anal., 2020
Model-agnostic Feature Importance and Effects with Dependent Features - A Conditional Subgroup Approach.
CoRR, 2020
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
Proceedings of the ECML PKDD 2020 Workshops, 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020
Proceedings of the 25th International Conference on Pattern Recognition, 2020
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
Proceedings of the xxAI - Beyond Explainable AI, 2020
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
2019
J. Open Source Softw., 2019
J. Mach. Learn. Res., 2019
Comput. Stat., 2019
Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection.
CoRR, 2019
Benchmarking time series classification - Functional data vs machine learning approaches.
CoRR, 2019
Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks.
CoRR, 2019
ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning.
CoRR, 2019
Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition.
CoRR, 2019
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions.
Proceedings of the Intelligent Systems and Applications, 2019
2018
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.
Stat. Comput., 2018
J. Open Source Softw., 2018
Corrigendum to "Probing for Sparse and Fast Variable Selection with Model-Based Boosting".
Comput. Math. Methods Medicine, 2018
Adv. Data Anal. Classif., 2018
Proceedings of the Eleventh International Symposium on Combinatorial Search, 2018
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018
2017
CoRR, 2017
Comput. Math. Methods Medicine, 2017
RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization.
Proceedings of the Learning and Intelligent Optimization - 11th International Conference, 2017
Proceedings of the Genetic and Evolutionary Computation Conference, 2017
Proceedings of the Evolutionary Multi-Criterion Optimization, 2017
2016
Multi-objective parameter configuration of machine learning algorithms using model-based optimization.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016
Proceedings of the Learning and Intelligent Optimization - 10th International Conference, 2016
Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study.
Proceedings of the 16th ITAT Conference Information Technologies, 2016
2015
Applying Model-Based Optimization to Hyperparameter Optimization in Machine Learning.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
Proceedings of the 4th International Workshop on Big Data, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
The Impact of Initial Designs on the Performance of MATSuMoTo on the Noiseless BBOB-2015 Testbed: A Preliminary Study.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015
Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015
Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2015
2014
PhD thesis, 2014
Proceedings of the Operations Research Proceedings 2014, 2014
Proceedings of the Learning and Intelligent Optimization, 2014
Proceedings of the Analysis of Large and Complex Data, 2014
Proceedings of the Analysis of Large and Complex Data, 2014
2013
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem.
Ann. Math. Artif. Intell., 2013
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
Proceedings of the Learning and Intelligent Optimization - 7th International Conference, 2013
A feature-based comparison of local search and the christofides algorithm for the travelling salesperson problem.
Proceedings of the Foundations of Genetic Algorithms XII, 2013
2012
Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary Computation.
Evol. Comput., 2012
A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem
CoRR, 2012
Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012
Statistical Comparison of Classifiers for Multi-objective Feature Selection in Instrument Recognition.
Proceedings of the Data Analysis, Machine Learning and Knowledge Discovery, 2012
Proceedings of the Data Analysis, Machine Learning and Knowledge Discovery, 2012
Proceedings of the Data Analysis, Machine Learning and Knowledge Discovery, 2012
Algorithm selection based on exploratory landscape analysis and cost-sensitive learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012
2011
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
2010
Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation.
Proceedings of the Parallel Problem Solving from Nature, 2010
Proceedings of the Challenges at the Interface of Data Analysis, Computer Science, and Optimization - Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21, 2010
Proceedings of the Challenges at the Interface of Data Analysis, Computer Science, and Optimization - Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21, 2010
Proceedings of the 9. ITG-Fachtagung Sprachkommunikation 2010, 2010
2009
Eng. Appl. Artif. Intell., 2009