Dan Garber

20 papers and 140 indexed citations i.

About

Dan Garber is a scholar working on Artificial Intelligence, Computational Mechanics and Management Science and Operations Research. According to data from OpenAlex, Dan Garber has authored 20 papers receiving a total of 140 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 14 papers in Computational Mechanics and 8 papers in Management Science and Operations Research. Recurrent topics in Dan Garber’s work include Sparse and Compressive Sensing Techniques (14 papers), Stochastic Gradient Optimization Techniques (10 papers) and Advanced Bandit Algorithms Research (8 papers). Dan Garber is often cited by papers focused on Sparse and Compressive Sensing Techniques (14 papers), Stochastic Gradient Optimization Techniques (10 papers) and Advanced Bandit Algorithms Research (8 papers). Dan Garber collaborates with scholars based in Israel, United States and Japan. Dan Garber's co-authors include Elad Hazan, Nathan Srebro, Edo Liberty, Tengyu Ma, Weiran Wang, Christos Boutsidis, Zohar Karnin, Jialei Wang, Ofer Meshi and Yakov Babichenko and has published in prestigious journals such as Mathematical Programming, SIAM Journal on Optimization and Mathematics of Operations Research.

In The Last Decade

Co-authorship network of co-authors of Dan Garber i

Fields of papers citing papers by Dan Garber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Dan Garber

Since Specialization
Citations

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

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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