This map shows the geographic impact of Samet Oymak'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 Samet Oymak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samet Oymak more than expected).
This network shows the impact of papers produced by Samet Oymak. 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 Samet Oymak. The network helps show where Samet Oymak may publish in the future.
Co-authorship network of co-authors of Samet Oymak
This figure shows the co-authorship network connecting the top 25 collaborators of Samet Oymak.
A scholar is included among the top collaborators of Samet Oymak 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 Samet Oymak. Samet Oymak is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Oymak, Samet, et al.. (2021). A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models. International Conference on Artificial Intelligence and Statistics. 3601–3609.1 indexed citations
Li, Mingchen, Mahdi Soltanolkotabi, & Samet Oymak. (2019). Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks. International Conference on Artificial Intelligence and Statistics. 4313–4324.6 indexed citations
Thrampoulidis, Christos, Samet Oymak, & Babak Hassibi. (2015). Regularized Linear Regression: A Precise Analysis of the Estimation Error. CaltechAUTHORS (California Institute of Technology). 1683–1709.59 indexed citations
16.
Oymak, Samet, et al.. (2014). Graph Clustering With Missing Data: Convex Algorithms and Analysis. Neural Information Processing Systems. 27. 2996–3004.16 indexed citations
17.
Oymak, Samet & Babak Hassibi. (2013). Asymptotically Exact Denoising in Relation to Compressed Sensing. arXiv (Cornell University).4 indexed citations
Oymak, Samet, Karthik Mohan, Maryam Fazel, & Babak Hassibi. (2011). A Simplified Approach to Recovery Conditions for
\nLow Rank Matrices. CaltechAUTHORS (California Institute of Technology).47 indexed citations
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.