Ofer Meshi

513 citations
16 papers · 163 · h-index 8

Impact in

Papers in

Ofer Meshi

16 papers receiving 156 citations

Peers

Ofer Meshi
Comparison fields: 5 of 48
  • Computational Mathematics 2
  • Artificial Intelligence 107
  • Computer Vision and Pattern Recognition 29
  • Computer Networks and Communications 26
  • Signal Processing 10
Replace Marvin Künnemann with:
Marvin Künnemann Germany
Nadia Essoussi Tunisia
Vladimir Nikulin Australia
Peter Haider Germany
Antonio Vergari Italy
Soeren Sonnenburg Germany
Egidio L. Terra Canada
Vikram Nitin United States
Marcin Kubica Poland
Su-In Lee United States
Ofer Meshi relative to Marvin Künnemann Germany Marvin Künnemann's profile →
Citations per field
00.5×1.5×2.2×
Marvin Künnemann · 1×
Citations per year

Countries citing papers authored by Ofer Meshi

Since Specialization
Citations

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).

Fields of papers citing papers by Ofer Meshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 22 scholars most cited alongside Ofer Meshi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ofer Meshi Line = papers co-authored together Ofer Meshi links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 200741
2
Learning Efficiently with Approximate Inference via Dual Losses
201035
3 201220
4
Convergence Rate Analysis of MAP Coordinate Minimization Algorithms
201213
5
More data means less inference: A pseudo-max approach to structured learning
201010
6
Learning Structured Models with the AUC Loss and Its Generalizations
20149
7
FastInf: An Efficient Approximate Inference Library
20108
8
Smooth and strong: MAP inference with linear convergence
20158
9
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes
20164
10
Efficient Training of Structured SVMs via Soft Constraints
20153
11
Approximate Linear Programming for Logistic Markov Decision Processes
20173
12 20242
13
Asynchronous Parallel Coordinate Minimization for MAP Inference
20172
14 20182
15 20172
16 20131

About Ofer Meshi

Ofer Meshi is a scholar working on Artificial Intelligence, Computer Networks and Communications, Management Science and Operations Research, Information Systems and Computational Mechanics, having authored 16 papers that have together received 163 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (6 papers), Machine Learning and Algorithms (6 papers), Error Correcting Code Techniques (4 papers), Bayesian Modeling and Causal Inference (3 papers), Neural Networks and Applications (2 papers), Advanced Bandit Algorithms Research (2 papers), Recommender Systems and Techniques (2 papers) and Sparse and Compressive Sensing Techniques (2 papers). The work is most often cited by research in Computational Mathematics (2 citations), Artificial Intelligence (107 citations), Computer Vision and Pattern Recognition (29 citations), Computer Networks and Communications (26 citations) and Signal Processing (10 citations). Ofer Meshi has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Amir Globerson, Tommi Jaakkola, Eytan Ruppin, Tomer Shlomi, David Sontag, Ariel Jaimovich, Nir Friedman, Alexander G. Schwing, Gal Elidan and Mehrdad Mahdavi. Their work appears in journals such as Journal of Machine Learning Research, BMC Systems Biology, International Conference on Artificial Intelligence and Statistics, arXiv (Cornell University) and Neural Information Processing Systems.

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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