This map shows the geographic impact of Amin Karbasi'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 Amin Karbasi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amin Karbasi more than expected).
This network shows the impact of papers produced by Amin Karbasi. 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 Amin Karbasi. The network helps show where Amin Karbasi may publish in the future.
Co-authorship network of co-authors of Amin Karbasi
This figure shows the co-authorship network connecting the top 25 collaborators of Amin Karbasi.
A scholar is included among the top collaborators of Amin Karbasi 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 Amin Karbasi. Amin Karbasi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Mingrui, Zebang Shen, Aryan Mokhtari, Hamed Hassani, & Amin Karbasi. (2020). One Sample Stochastic Frank-Wolfe.. International Conference on Artificial Intelligence and Statistics. 4012–4023.2 indexed citations
4.
Bhaskara, Aditya, Amin Karbasi, Silvio Lattanzi, & Morteza Zadimoghaddam. (2020). Online MAP Inference of Determinantal Point Processes. Neural Information Processing Systems. 33. 3419–3429.
5.
Kazemi, Ehsan, et al.. (2019). Adaptive Sequence Submodularity. Neural Information Processing Systems. 32. 5353–5364.2 indexed citations
6.
Karbasi, Amin, Hamed Hassani, Aryan Mokhtari, & Zebang Shen. (2019). Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. Neural Information Processing Systems. 32. 13066–13076.1 indexed citations
7.
Kazemi, Ehsan, et al.. (2019). Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. International Conference on Machine Learning. 3311–3320.4 indexed citations
Feldman, Moran, Amin Karbasi, & Ehsan Kazemi. (2018). Do Less, Get More: Streaming Submodular Maximization with Subsampling. arXiv (Cornell University). 31. 730–740.1 indexed citations
10.
Kazemi, Ehsan, et al.. (2018). Data Summarization at Scale: A Two-Stage Submodular Approach. arXiv (Cornell University). 3593–3602.6 indexed citations
11.
Kazemi, Ehsan, Morteza Zadimoghaddam, & Amin Karbasi. (2018). Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints. International Conference on Machine Learning. 2544–2553.14 indexed citations
12.
Zadimoghaddam, Morteza, et al.. (2017). Probabilistic Submodular Maximization in Sub-Linear Time.. International Conference on Machine Learning. 3241–3250.7 indexed citations
13.
Hassani, S. Hamed, Mahdi Soltanolkotabi, & Amin Karbasi. (2017). Gradient Methods for Submodular Maximization. Neural Information Processing Systems. 30. 5841–5851.4 indexed citations
14.
Bun, Mark, et al.. (2017). Differentially Private Submodular Maximization: Data Summarization in Disguise.. International Conference on Machine Learning. 70. 2478–2487.5 indexed citations
15.
Mirzasoleiman, Baharan, Morteza Zadimoghaddam, & Amin Karbasi. (2016). Fast Distributed Submodular Cover: Public-Private Data Summarization. Neural Information Processing Systems. 29. 3594–3602.21 indexed citations
16.
Chen, Yuxin, S. Hamed Hassani, Amin Karbasi, & Andreas Krause. (2015). Sequential Information Maximization: When is Greedy Near-optimal?. Conference on Learning Theory. 338–363.12 indexed citations
17.
Rebeschini, Patrick & Amin Karbasi. (2015). Fast Mixing for Discrete Point Processes. Conference on Learning Theory. 1480–1500.2 indexed citations
18.
Karbasi, Amin, et al.. (2013). Iterative Learning and Denoising in Convolutional Neural Associative Memories. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 28(1). 445–453.10 indexed citations
19.
Singla, Adish, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, & Andreas Krause. (2013). On Actively Teaching the Crowd to Classify. Infoscience (Ecole Polytechnique Fédérale de Lausanne).5 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.