Ronald Ortner

2.4k citations
26 papers · 495 indexed · h-index 9

Ronald Ortner

23 papers receiving 454 citations

Peers

Ronald Ortner
Comparison fields: 5 of 57
  • Management Science and Operations Research 298
  • Artificial Intelligence 350
  • Computer Networks and Communications 103
  • Computational Theory and Mathematics 52
  • General Decision Sciences 6
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Countries citing papers authored by Ronald Ortner

Since Specialization
Citations

This map shows the geographic impact of Ronald Ortner'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 Ronald Ortner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronald Ortner more than expected).

Fields of papers citing papers by Ronald Ortner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronald Ortner. 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 Ronald Ortner. The network helps show where Ronald Ortner may publish in the future.

Co-authorship network

The 22 scholars most cited alongside Ronald Ortner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ronald Ortner Line = papers co-authored together Ronald Ortner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20224
2 20221
3 20205
4
Variational Regret Bounds for Reinforcement Learning
20195
5
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information
20191
6 20161
7
Pareto Front Identification from Stochastic Bandit Feedback
201613
8
Algorithmic Learning Theory: 27th International Conference, ALT 2016 Bari, Italy, October 19-21, 2016 Proceedings
20163
9 20149
10 201212
11
PAC-Bayesian Analysis of Contextual Bandits
201119
12
Near-optimal Regret Bounds for Reinforcement Learning
2010198
13 20107
14 20102
15 2010110
16
Near-optimal Regret Bounds for Reinforcement Learning
200856
17 20082
18 20071
19 20071
20
An arrangement of pseudocircles not realizable with circles
20052

About Ronald Ortner

Ronald Ortner is a scholar working on Management Science and Operations Research, Discrete Mathematics and Combinatorics and Computer Graphics and Computer-Aided Design, having authored 26 papers that have together received 495 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (13 papers), Reinforcement Learning in Robotics (12 papers), Machine Learning and Algorithms (5 papers), Optimization and Search Problems (3 papers), Smart Grid Energy Management (3 papers), Computational Geometry and Mesh Generation (2 papers), Modular Robots and Swarm Intelligence (1 paper) and Graph theory and applications (1 paper). The work is most often cited by research in Management Science and Operations Research (298 citations), Artificial Intelligence (350 citations) and Computer Networks and Communications (103 citations). Ronald Ortner has collaborated with scholars based in Austria, United States and Germany. Frequent co-authors include Peter Auer, Wolfgang Woess, Pratik Gajane, John Shawe‐Taylor, François Laviolette, Yevgeny Seldin, Chao-Kai Chiang, Mădălina M. Drugan, Rémi Munos and Daniil Ryabko. Their work appears in journals such as Minds and Machines, Theoretical Computer Science, Annals of Operations Research, Machine Learning and Canadian Journal of Mathematics.

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.

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