Samet Oymak

2.6k citations
57 papers · 736 indexed · h-index 13
Topics
Sparse and Compressive Sensing Techniques (20 papers)Blind Source Separation Techniques (8 papers)Image and Signal Denoising Methods (7 papers)

In The Last Decade

Samet Oymak

51 papers receiving 709 citations

Peers

Samet Oymak
Comparison fields: 5 of 75
  • Computational Mechanics 308
  • Computer Vision and Pattern Recognition 202
  • Artificial Intelligence 202
  • Radiation 151
  • Signal Processing 110
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Citations per field
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Countries citing papers authored by Samet Oymak

Since Specialization
Citations

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).

Fields of papers citing papers by Samet Oymak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 3
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5 1
6 2
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8
A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models
1
9 5
10 2
11
Finite Sample System Identification: Optimal Rates and the Role of Regularization.
6
12 65
13
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
6
14 1
15
Regularized Linear Regression: A Precise Analysis of the Estimation Error
59
16
Graph Clustering With Missing Data: Convex Algorithms and Analysis
16
17
Asymptotically Exact Denoising in Relation to Compressed Sensing
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18 11
19 0
20
A Simplified Approach to Recovery Conditions for \nLow Rank Matrices
47

About Samet Oymak

Samet Oymak is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 57 papers that have together received 736 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (20 papers), Blind Source Separation Techniques (8 papers) and Image and Signal Denoising Methods (7 papers). The work is most often cited by research in Computational Mathematics (20 citations), Structural Biology (40 citations) and Radiation (151 citations). Samet Oymak has collaborated with scholars based in United States, Türkiye and Australia. Frequent co-authors include Babak Hassibi, Kishore Jaganathan, Maryam Fazel, Mahdi Soltanolkotabi, Amin Jalali, Yonina C. Eldar, Christos Thrampoulidis, Necmiye Özay, Karthik Mohan and Jiasi Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and IEEE Transactions on Information Theory.

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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