Ibrahim Alabdulmohsin
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Signal Processing
- Electrical and Electronic Engineering
- Co-authors
- Xin GaoXiangliang ZhangА. И. КолесниковMathilde CaronPavel IzmailovXiaohua ZhaiLucas BeyerMichael Tschannen
- Topics
- Machine Learning and Algorithms (6 papers)Machine Learning and Data Classification (3 papers)Neural Networks and Applications (2 papers)
- Journals
- Machine LearningEntropyArabian Journal of Mathematics
- Partner nations
- Saudi ArabiaUnited StatesSwitzerland
In The Last Decade
Ibrahim Alabdulmohsin
13 papers receiving 133 citations
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 73
- Computer Vision and Pattern Recognition 37
- Computer Networks and Communications 30
- Signal Processing 27
- Electrical and Electronic Engineering 15
Countries citing papers authored by Ibrahim Alabdulmohsin
This map shows the geographic impact of Ibrahim Alabdulmohsin'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 Ibrahim Alabdulmohsin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahim Alabdulmohsin more than expected).
Fields of papers citing papers by Ibrahim Alabdulmohsin
This network shows the impact of papers produced by Ibrahim Alabdulmohsin. 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 Ibrahim Alabdulmohsin. The network helps show where Ibrahim Alabdulmohsin may publish in the future.
Co-authorship network of co-authors of Ibrahim Alabdulmohsin
This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahim Alabdulmohsin. A scholar is included among the top collaborators of Ibrahim Alabdulmohsin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ibrahim Alabdulmohsin. Ibrahim Alabdulmohsin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 43 | |
| 3 | 0 | |
| 4 | What Do Neural Networks Learn When Trained With Random Labels | 1 |
| 5 | 3 | |
| 6 | Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization | 2 |
| 7 | 7 | |
| 8 | An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability | 6 |
| 9 | 1 | |
| 10 | 10 | |
| 11 | 6 | |
| 12 | Algorithmic stability and uniform generalization | 7 |
| 13 | 10 | |
| 14 | Support vector machines with indefinite kernels | 12 |
| 15 | 6 | |
| 16 | 23 |
About Ibrahim Alabdulmohsin
Ibrahim Alabdulmohsin is a scholar working on Discrete Mathematics and Combinatorics, Artificial Intelligence and Algebra and Number Theory, having authored 16 papers that have together received 137 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computational Mathematics (3 citations), Signal Processing (27 citations) and Artificial Intelligence (73 citations). Ibrahim Alabdulmohsin has collaborated with scholars based in Saudi Arabia, United States and Switzerland. Frequent co-authors include Xin Gao, Xiangliang Zhang, А. И. Колесников, Mathilde Caron, Pavel Izmailov, Xiaohua Zhai, Lucas Beyer, Michael Tschannen, Filip Pavetic and Matthias Minderer. Their work appears in journals such as Machine Learning, Entropy and Arabian 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.