This map shows the geographic impact of Ofer Meshi'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 Ofer Meshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ofer Meshi more than expected).
This network shows the impact of papers produced by Ofer Meshi. 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 Ofer Meshi. The network helps show where Ofer Meshi may publish in the future.
Co-authorship network of co-authors of Ofer Meshi
This figure shows the co-authorship network connecting the top 25 collaborators of Ofer Meshi.
A scholar is included among the top collaborators of Ofer Meshi 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 Ofer Meshi. Ofer Meshi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Garber, Dan & Ofer Meshi. (2016). Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes. arXiv (Cornell University). 29. 1001–1009.4 indexed citations
7.
Meshi, Ofer, Nathan Srebro, & Tamir Hazan. (2015). Efficient Training of Structured SVMs via Soft Constraints. International Conference on Artificial Intelligence and Statistics. 699–707.3 indexed citations
8.
Meshi, Ofer, Mehrdad Mahdavi, & Alexander G. Schwing. (2015). Smooth and strong: MAP inference with linear convergence. Neural Information Processing Systems. 28. 298–306.8 indexed citations
9.
Meshi, Ofer, et al.. (2014). Learning Structured Models with the AUC Loss and Its Generalizations. International Conference on Artificial Intelligence and Statistics. 841–849.9 indexed citations
10.
Meshi, Ofer, Elad Eban, Gal Elidan, & Amir Globerson. (2013). Learning Max-Margin Tree Predictors. arXiv (Cornell University). 411–420.1 indexed citations
11.
Meshi, Ofer, Amir Globerson, & Tommi Jaakkola. (2012). Convergence Rate Analysis of MAP Coordinate Minimization Algorithms. DSpace@MIT (Massachusetts Institute of Technology). 25. 3014–3022.13 indexed citations
Sontag, David, Ofer Meshi, Amir Globerson, & Tommi Jaakkola. (2010). More data means less inference: A pseudo-max approach to structured learning. DSpace@MIT (Massachusetts Institute of Technology). 23. 2181–2189.10 indexed citations
14.
Jaimovich, Ariel, Ofer Meshi, Ian McGraw, & Gal Elidan. (2010). FastInf: An Efficient Approximate Inference Library. Journal of Machine Learning Research. 11(57). 1733–1736.8 indexed citations
15.
Meshi, Ofer, David Sontag, Amir Globerson, & Tommi Jaakkola. (2010). Learning Efficiently with Approximate Inference via Dual Losses. DSpace@MIT (Massachusetts Institute of Technology). 783–790.35 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.