Marcel Wever

Follow

Generating author description...

All published works
Action Title Year Authors
+ Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction 2024 Stefan Heid
Marcel Wever
Eyke Hüllermeier
+ PDF Chat ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data 2024 Valentin Margraf
Marcel Wever
Sandra Gilhuber
Gabriel Marques Tavares
Thomas Seidl
Eyke Hüllermeier
+ PDF Chat Position Paper: Rethinking Empirical Research in Machine Learning: Addressing Epistemic and Methodological Challenges of Experimentation 2024 Moritz Herrmann
F. Julian D. Lange
Katharina Eggensperger
Giuseppe Casalicchio
Marcel Wever
Matthias Feurer
David Rügamer
Eyke Hüllermeier
Anne‐Laure Boulesteix
Bernd Bischl
+ PDF Chat Automated Machine Learning for Multi-Label Classification 2024 Marcel Wever
+ Information Leakage Detection through Approximate Bayes-optimal Prediction 2024 Pritha Gupta
Marcel Wever
Eyke Hüllermeier
+ PDF Chat Information Leakage Detection Through Approximate Bayes-Optimal Prediction 2024 Pritha Gupta
Marcel Wever
Eyke Hüllermeier
+ PDF Chat Annotation uncertainty in the context of grammatical change 2023 Marie-Luis Merten
Marcel Wever
Michaela Geierhos
Doris Tophinke
Eyke Hüllermeier
+ PDF Chat Towards Green Automated Machine Learning: Status Quo and Future Directions 2023 Tanja Tornede
Alexander Tornede
Jonas Hanselle
Felix Mohr
Marcel Wever
Eyke Hüllermeier
+ PDF Chat PyExperimenter: Easily distribute experiments and track results 2023 Tanja Tornede
Alexander Tornede
Lukas Fehring
Lukas Gehring
Helena Graf
Jonas Hanselle
Felix Mohr
Marcel Wever
+ PyExperimenter: Easily distribute experiments and track results 2023 Tanja Tornede
Alexander Tornede
Lukas Fehring
Lukas Gehring
Helena Graf
Jonas Hanselle
Felix Mohr
Marcel Wever
+ Iterative Deepening Hyperband 2023 Jasmin Brandt
Marcel Wever
D. Iliadis
Viktor Bengs
Eyke Hüllermeier
+ PDF Chat A Survey of Methods for Automated Algorithm Configuration 2022 Elias Schede
Jasmin Brandt
Alexander Tornede
Marcel Wever
Viktor Bengs
Eyke Hüllermeier
Kevin Tierney
+ A Survey of Methods for Automated Algorithm Configuration 2022 Elias Schede
Jasmin Brandt
Alexander Tornede
Marcel Wever
Viktor Bengs
Eyke Hüllermeier
Kevin Tierney
+ Hyperparameter optimization in deep multi-target prediction 2022 D. Iliadis
Marcel Wever
Bernard De Baets
Willem Waegeman
+ Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets 2022 David Schubert
Pritha Gupta
Marcel Wever
+ PDF Chat Naive Automated Machine Learning 2021 Felix Mohr
Marcel Wever
+ PDF Chat Towards Green Automated Machine Learning: Status Quo and Future Directions 2021 Tanja Tornede
Alexander Tornede
Jonas Hanselle
Marcel Wever
Felix Mohr
Eyke Hüllermeier
+ Naive Automated Machine Learning -- A Late Baseline for AutoML 2021 Felix Mohr
Marcel Wever
+ Automated Machine Learning, Bounded Rationality, and Rational Metareasoning 2021 Eyke Hüllermeier
Felix Mohr
Alexander Tornede
Marcel Wever
+ Algorithm Selection on a Meta Level 2021 Alexander Tornede
Lukas Gehring
Tanja Tornede
Marcel Wever
Eyke Hüllermeier
+ Towards Green Automated Machine Learning: Status Quo and Future Directions 2021 Tanja Tornede
Alexander Tornede
Jonas Hanselle
Marcel Wever
Felix Mohr
Eyke Hüllermeier
+ Naive Automated Machine Learning 2021 Felix Mohr
Marcel Wever
+ Annotation Uncertainty in the Context of Grammatical Change 2021 Marie-Luis Merten
Marcel Wever
Michaela Geierhos
Doris Tophinke
Eyke Hüllermeier
+ Towards Meta-Algorithm Selection. 2020 Alexander Tornede
Marcel Wever
Eyke Hüllermeier
+ Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis 2020 Alexander Tornede
Marcel Wever
Stefan Werner
Felix Mohr
Eyke Hüllermeier
+ PDF Chat Extreme Algorithm Selection with Dyadic Feature Representation 2020 Alexander Tornede
Marcel Wever
Eyke Hüllermeier
+ Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction 2020 Stefan Heid
Marcel Wever
Eyke Hüllermeier
+ Towards Meta-Algorithm Selection 2020 Alexander Tornede
Marcel Wever
Eyke Hüllermeier
+ A Flexible Class of Dependence-aware Multi-Label Loss Functions 2020 Eyke Hüllermeier
Marcel Wever
Eneldo Loza Mencía
Johannes Fürnkranz
Michael A. Rapp
+ Automated machine learning service composition 2018 Felix Mohr
Marcel Wever
Eyke Hüllermeier
+ Automated Multi-Label Classification based on ML-Plan 2018 Marcel Wever
Felix Mohr
Eyke Hüllermeier
+ Automated Machine Learning Service Composition 2018 Felix Mohr
Marcel Wever
Eyke Hüllermeier
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ Automated Algorithm Selection: Survey and Perspectives 2018 Pascal Kerschke
Holger H. Hoos
Frank Neumann
Heike Trautmann
4
+ ASlib: A benchmark library for algorithm selection 2016 Bernd Bischl
Pascal Kerschke
Lars Kotthoff
Marius Lindauer
Yuri Malitsky
Alexandre Fréchette
Holger H. Hoos
Frank Hutter
Kevin Leyton‐Brown
Kevin Tierney
3
+ PDF Chat OpenML 2014 Joaquin Vanschoren
Jan N. van Rijn
Bernd Bischl
Luı́s Torgo
3
+ Consistent Algorithms for Multiclass Classification with a Reject Option 2015 Harish G. Ramaswamy
Ambuj Tewari
Shivani Agarwal
2
+ Evaluating credal classifiers by utility-discounted predictive accuracy 2012 Marco Zaffalon
Giorgio Corani
Denis Deratani Mauá
2
+ Bidirectional LSTM-CRF Models for Sequence Tagging 2015 Zhiheng Huang
Wei Xu
Kai Yu
2
+ Practical Bayesian Optimization of Machine Learning Algorithms 2012 Jasper Snoek
Hugo Larochelle
Ryan P. Adams
2
+ A tutorial on conformal prediction 2007 Glenn Shafer
Vladimir Vovk
2
+ Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization 2013 Eyke Hüllermeier
2
+ PDF Chat Extreme Algorithm Selection with Dyadic Feature Representation 2020 Alexander Tornede
Marcel Wever
Eyke Hüllermeier
2
+ PDF Chat SUNNY: a Lazy Portfolio Approach for Constraint Solving 2014 Roberto Amadini
Maurizio Gabbrielli
Jacopo Mauro
2
+ Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis 2020 Alexander Tornede
Marcel Wever
Stefan Werner
Felix Mohr
Eyke Hüllermeier
2
+ The Costs of Indeterminacy: How to Determine Them? 2016 Gen Yang
Sébastien Destercke
Marie-Hélène Masson
2
+ PDF Chat ParamILS: An Automatic Algorithm Configuration Framework 2009 Frank Hutter
Holger H. Hoos
Kevin Leyton‐Brown
T. Stuetzle
2
+ Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms 2012 Chris Thornton
Frank Hutter
Holger H. Hoos
Kevin Leyton‐Brown
2
+ PDF Chat Benchmark and Survey of Automated Machine Learning Frameworks 2021 Marc-André Zöller
Marco F. Huber
2
+ Efficient Algorithms for Set-Valued Prediction in Multi-Class Classification. 2019 Thomas Mortier
Marek Wydmuch
Eyke Hüllermeier
Krzysztof Dembczyński
Willem Waegeman
2
+ PDF Chat Generalized evidence theory 2015 Yong Deng
1
+ PDF Chat Restart Strategy Selection Using Machine Learning Techniques 2009 Shai Haim
Toby Walsh
1
+ The Emergence of Probability 2006 Ian Hacking
1
+ PDF Chat Message-Based Web Service Composition, Integrity Constraints, and Planning under Uncertainty: A New Connection 2009 Jörg Hoffmann
Piergiorgio Bertoli
Malte Helmert
Marco Pistore
1
+ DARTS: Differentiable Architecture Search 2018 Hanxiao Liu
Karen Simonyan
Yiming Yang
1
+ PDF Chat Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science 2016 Randal S. Olson
Nathan Bartley
Ryan J. Urbanowicz
Jason H. Moore
1
+ Scikit-learn: Machine Learning in Python 2012 Fabián Pedregosa
Gaël Varoquaux
Alexandre Gramfort
Vincent Michel
Bertrand Thirion
Olivier Grisel
Mathieu Blondel
Peter Prettenhofer
Ron J. Weiss
Vincent Dubourg
1
+ Neural Architecture Search with Reinforcement Learning 2016 Barret Zoph
Quoc V. Le
1
+ Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization 2016 Lisha Li
Kevin Jamieson
Giulia DeSalvo
Afshin Rostamizadeh
Ameet Talwalkar
1
+ PDF Chat Algorithm Selection for Combinatorial Search Problems: A Survey 2014 Lars Kotthoff
1
+ PDF Chat Zero-Shot Learning — The Good, the Bad and the Ugly 2017 Yongqin Xian
Bernt Schiele
Zeynep Akata
1
+ Multi-fidelity Bayesian Optimisation with Continuous Approximations 2017 Kirthevasan Kandasamy
Gautam Dasarathy
Jeff Schneider
Barnabás Póczos
1
+ Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start 2017 Valerio Perrone
Rodolphe Jenatton
Matthias Seeger
Cédric Archambeau
1
+ Freeze-Thaw Bayesian Optimization 2014 Kevin Swersky
Jasper Snoek
Ryan P. Adams
1
+ OBOE 2019 Chengrun Yang
Yuji Akimoto
Dae Won Kim
Madeleine Udell
1
+ AMC: AutoML for Model Compression and Acceleration on Mobile Devices 2018 Yihui He
Ji Lin
Zhijian Liu
Hanrui Wang
Li-Jia Li
Song Han
1
+ PDF Chat Possibility theory and statistical reasoning 2006 Didier Dubois
1
+ Natural Language Processing (almost) from Scratch 2011 Ronan Collobert
Jason Weston
Léon Bottou
Michael Karlen
Koray Kavukcuoglu
Pavel P. Kuksa
1
+ Meta-Learning: A Survey 2018 Joaquin Vanschoren
1
+ PDF Chat No free lunch theorems for optimization 1997 David H. Wolpert
William G. Macready
1
+ Maxitive measure and integration 1971 Niel Shilkret
1
+ PDF Chat The algorithm selection competitions 2015 and 2017 2019 Marius Lindauer
Jan N. van Rijn
Lars Kotthoff
1
+ Benchmarking Automatic Machine Learning Frameworks 2018 Adithya Balaji
Alexander G. Allen
1
+ Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning 2019 Jian Wu
Saul Toscano-Palmerin
Peter I. Frazier
Andrew Gordon Wilson
1
+ Generalizing from a Few Examples: A Survey on Few-Shot Learning 2019 Yaqing Wang
Quanming Yao
James T. Kwok
Lionel M. Ni
1
+ PDF Chat AMC: AutoML for Model Compression and Acceleration on Mobile Devices 2018 Yihui He
Ji Lin
Zhijian Liu
Hanrui Wang
Li-Jia Li
Song Han
1
+ TnT - A Statistical Part-of-Speech Tagger 2000 Thorsten Brants
1
+ PDF Chat Designing adaptive neural networks for energy-constrained image classification 2018 Dimitrios Stamoulis
Ting-Wu Chin
Anand Krishnan Prakash
Haocheng Fang
Sribhuvan Sajja
Mitchell Bognar
Diana Marculescu
1
+ PDF Chat Improving Lemmatization of Non-Standard Languages with Joint Learning 2019 Enrique Manjavacas
Ákos Kádár
Mike Kestemont
1
+ PDF Chat SATzilla: Portfolio-based Algorithm Selection for SAT 2008 Lizhong Xu
Frank Hutter
Holger H. Hoos
Kevin Leyton‐Brown
1
+ Neural Architecture Search: A Survey 2018 Thomas Elsken
Jan Hendrik Metzen
Frank Hutter
1
+ A Tutorial on Bayesian Optimization 2018 Peter I. Frazier
1
+ Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings 2018 Bernd Bohnet
Ryan McDonald
Gonçalo Simões
Daniel Andor
Emily Pitler
Joshua Maynez
1