Oliver Hinder
Impact in
- Numerical Analysis top 10%
- Advanced Optimization Algorithms Research
- Computational Mechanics top 10%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Advanced Optimization Algorithms Research 7
-
- Optimization and Variational Analysis 3
- Matrix Theory and Algorithms 2
- Co-authors
- Aaron Sidford (1 shared paper)John C. Duchi (2 shared papers)Yair Carmon (1 shared paper)Andrew Mason (1 shared paper)Yinyu Ye (4 shared papers)Haihao Lu (1 shared paper)Gabriel Haeser (1 shared paper)David Applegate (1 shared paper)
- Journals
- Mathematical Programming (2 papers)SIAM Journal on Optimization (1 paper)Mathematics of Operations Research (1 paper)Operations Research (1 paper)Operations Research Letters (1 paper)
- Partner nations
- United StatesUnited KingdomNew Zealand
In The Last Decade
Oliver Hinder
5 papers receiving 117 citations
Peers
Comparison fields: 5 of 36
- Numerical Analysis 43
- Computational Mechanics 67
- Computational Theory and Mathematics 37
- Artificial Intelligence 64
- Industrial and Manufacturing Engineering 17
Countries citing papers authored by Oliver Hinder
This map shows the geographic impact of Oliver Hinder'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 Oliver Hinder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver Hinder more than expected).
Fields of papers citing papers by Oliver Hinder
This network shows the impact of papers produced by Oliver Hinder. 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 Oliver Hinder. The network helps show where Oliver Hinder may publish in the future.
Co-authors
The 13 scholars most cited alongside Oliver Hinder, 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 | 2018 | 86 | |
| 2 | 2017 | 16 | |
| 3 | 2022 | 15 | |
| 4 | 2019 | 13 | |
| 5 | An efficient nonconvex reformulation of stagewise convex optimization problems | 2020 | 1 |
| 6 | 2023 | 1 | |
| 7 | Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices | 2020 | 0 |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 |
About Oliver Hinder
Oliver Hinder is a scholar working on Numerical Analysis, Computational Theory and Mathematics, Computational Mechanics, Artificial Intelligence and Computer Networks and Communications, having authored 9 papers that have together received 132 indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (7 papers), Sparse and Compressive Sensing Techniques (4 papers), Optimization and Variational Analysis (3 papers), Stochastic Gradient Optimization Techniques (2 papers), Matrix Theory and Algorithms (2 papers), Optimization and Search Problems (1 paper), Scheduling and Optimization Algorithms (1 paper) and Optimization and Packing Problems (1 paper). The work is most often cited by research in Numerical Analysis (43 citations), Computational Mechanics (67 citations), Computational Theory and Mathematics (37 citations), Artificial Intelligence (64 citations) and Industrial and Manufacturing Engineering (17 citations). Oliver Hinder has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Aaron Sidford, John C. Duchi, Yair Carmon, Andrew Mason, Yinyu Ye, Haihao Lu, Gabriel Haeser, David Applegate, Miles Lubin and Srinadh Bhojanapalli. Their work appears in journals such as Mathematical Programming, SIAM Journal on Optimization, Mathematics of Operations Research, Operations Research and Operations Research Letters.
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.