Max Vladymyrov

750 total citations
9 papers, 91 citations indexed

About

Max Vladymyrov is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Max Vladymyrov has authored 9 papers receiving a total of 91 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Media Technology. Recurrent topics in Max Vladymyrov's work include Face and Expression Recognition (4 papers), Stochastic Gradient Optimization Techniques (3 papers) and Remote-Sensing Image Classification (3 papers). Max Vladymyrov is often cited by papers focused on Face and Expression Recognition (4 papers), Stochastic Gradient Optimization Techniques (3 papers) and Remote-Sensing Image Classification (3 papers). Max Vladymyrov collaborates with scholars based in United States and Spain. Max Vladymyrov's co-authors include Miguel Á. Carreira-Perpiñán, Andrey Zhmoginov, Andrew Jackson, M. Sandler and Nolan Miller and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Max Vladymyrov

9 papers receiving 87 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Max Vladymyrov United States	5	59	48	13	10	10	9	91
Valentin Khrulkov Russia	5	76 1.3×	95 2.0×	18 1.4×	4 0.4×	9 0.9×	9	150
Noah A. Smith United States	5	27 0.5×	69 1.4×	6 0.5×	7 0.7×	3 0.3×	11	119
Jeffrey De Fauw United States	2	63 1.1×	47 1.0×	3 0.2×	9 0.9×	6 0.6×	3	102
Madhav Nimishakavi India	5	32 0.5×	66 1.4×	21 1.6×	9 0.9×	4 0.4×	7	99
Pol Moreno United Kingdom	6	211 3.6×	76 1.6×	7 0.5×	12 1.2×	26 2.6×	7	242
Lazar Valkov United States	3	66 1.1×	57 1.2×	3 0.2×	3 0.3×	2 0.2×	3	107
Chang Guo China	5	50 0.8×	21 0.4×	7 0.5×	3 0.3×	6 0.6×	17	108
Assaf Arbelle United States	7	102 1.7×	117 2.4×	6 0.5×	5 0.5×	22 2.2×	11	195
Pierre-André Savalle France	2	17 0.3×	27 0.6×	8 0.6×	47 4.7×	7 0.7×	2	78

Countries citing papers authored by Max Vladymyrov

Since Specialization

Citations

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

Fields of papers citing papers by Max Vladymyrov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Vladymyrov

This figure shows the co-authorship network connecting the top 25 collaborators of Max Vladymyrov. A scholar is included among the top collaborators of Max Vladymyrov 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 Max Vladymyrov. Max Vladymyrov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Zhmoginov, Andrey, et al.. (2023). Decentralized Learning with Multi-Headed Distillation. 8053–8063. 1 indexed citations

2.

Sandler, M., Andrey Zhmoginov, Max Vladymyrov, & Andrew Jackson. (2022). Fine-tuning Image Transformers using Learnable Memory. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 12145–12154. 32 indexed citations

3.

Vladymyrov, Max & Miguel Á. Carreira-Perpiñán. (2017). Fast, accurate spectral clustering using locally linear landmarks. 3870–3879. 1 indexed citations

4.

Vladymyrov, Max & Miguel Á. Carreira-Perpiñán. (2016). The variational Nyström method for large-scale spectral problems. International Conference on Machine Learning. 211–220. 7 indexed citations

5.

Carreira-Perpiñán, Miguel Á. & Max Vladymyrov. (2015). A fast, universal algorithm to learn parametric nonlinear embeddings. Neural Information Processing Systems. 28. 253–261. 4 indexed citations

6.

Vladymyrov, Max & Miguel Á. Carreira-Perpiñán. (2014). Linear-time Training of Nonlinear Low-Dimensional Embeddings. International Conference on Artificial Intelligence and Statistics. 968–977. 9 indexed citations

7.

Vladymyrov, Max & Miguel Á. Carreira-Perpiñán. (2013). Entropic Affinities: Properties and Efficient Numerical Computation. International Conference on Machine Learning. 477–485. 21 indexed citations

8.

Vladymyrov, Max & Miguel Á. Carreira-Perpiñán. (2012). Fast Training of Nonlinear Embedding Algorithms.. International Conference on Machine Learning. 1 indexed citations

9.

Vladymyrov, Max, et al.. (2012). Partial-Hessian Strategies for Fast Learning of Nonlinear Embeddings. arXiv (Cornell University). 987–994. 15 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.

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