Marc Becker
Impact in
- Artificial Intelligence top 10%
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Metaheuristic Optimization Algorithms Research
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- Hydrological Forecasting Using AI
Papers in
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- Metaheuristic Optimization Algorithms Research 1
- Multi-Agent Systems and Negotiation 1
- Machine Learning and Data Classification 1
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- Business Process Modeling and Analysis 1
- Co-authors
- Michel Lang (1 shared paper)Theresa Ullmann (1 shared paper)Janek Thomas (1 shared paper)Difan Deng (1 shared paper)Tobias Pielok (1 shared paper)Bernd Bischl (1 shared paper)Marius Lindauer (1 shared paper)Stefan Coors (1 shared paper)
- Journals
- Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (1 paper)FreiDok plus (Universitätsbibliothek Freiburg) (1 paper)Digital Commons - University of South Florida (University of South Florida) (1 paper)
- Partner nations
- Germany
In The Last Decade
Marc Becker
5 papers receiving 464 citations
Marc Becker's Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 129
- Environmental Engineering 45
- Health Informatics 4
- Health Information Management 10
- Management Science and Operations Research 24
Countries citing papers authored by Marc Becker
This map shows the geographic impact of Marc Becker's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marc Becker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Becker more than expected).
Fields of papers citing papers by Marc Becker
This network shows the impact of papers produced by Marc Becker. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marc Becker. The network helps show where Marc Becker may publish in the future.
Co-authors
The 16 scholars most cited alongside Marc Becker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges Hit paper breakdown → | 2023 | 455 |
| 2 | José Carlos Mariátegui: An Anthology | 2011 | 12 |
| 3 | SAGA Geoprocessing and Terrain Analysis [R package RSAGA version 1.3.0] | 2018 | 7 |
| 4 | Intelligente Softwareagenten und betriebswirtschaftliche Anwendungsszenarien im Gesundheitswesen | 2003 | 1 |
| 5 | ArcGIS Geoprocessing via Python [R package RPyGeo version 1.0.0] | 2018 | 1 |
About Marc Becker
Marc Becker is a scholar working on Artificial Intelligence, Management Information Systems, Sociology and Political Science, Literature and Literary Theory and Computational Theory and Mathematics, having authored 5 papers that have together received 476 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (1 paper), Business Process Modeling and Analysis (1 paper), Access Control and Trust (1 paper), Cultural, Media, and Literary Studies (1 paper), Metaheuristic Optimization Algorithms Research (1 paper), Literature, Culture, and Criticism (1 paper), Multi-Agent Systems and Negotiation (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Artificial Intelligence (129 citations), Environmental Engineering (45 citations), Health Informatics (4 citations), Health Information Management (10 citations) and Management Science and Operations Research (24 citations). Marc Becker has collaborated with scholars based in Germany. Frequent co-authors include Michel Lang, Theresa Ullmann, Janek Thomas, Difan Deng, Tobias Pielok, Bernd Bischl, Marius Lindauer, Stefan Coors, Martin Binder and Anne‐Laure Boulesteix. Their work appears in journals such as Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, FreiDok plus (Universitätsbibliothek Freiburg) and Digital Commons - University of South Florida (University of South Florida).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.