Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Distributed Optimization Over Time-Varying Directed Graphs
2014740 citationsAlex Olshevsky et al.IEEE Transactions on Automatic Controlprofile →
Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs
Countries citing papers authored by Alex Olshevsky
Since
Specialization
Citations
This map shows the geographic impact of Alex Olshevsky'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 Alex Olshevsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Olshevsky more than expected).
This network shows the impact of papers produced by Alex Olshevsky. 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 Alex Olshevsky. The network helps show where Alex Olshevsky may publish in the future.
Co-authorship network of co-authors of Alex Olshevsky
This figure shows the co-authorship network connecting the top 25 collaborators of Alex Olshevsky.
A scholar is included among the top collaborators of Alex Olshevsky 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 Alex Olshevsky. Alex Olshevsky is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Olshevsky, Alex, Ioannis Ch. Paschalidis, & Shi Pu. (2019). Asymptotic Network Independence in Distributed Optimization for Machine Learning. arXiv (Cornell University).1 indexed citations
5.
Olshevsky, Alex, Ioannis Ch. Paschalidis, & Shi Pu. (2019). A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent. arXiv (Cornell University).6 indexed citations
Olshevsky, Alex & César A. Uribe. (2016). 1 Nonasymptotic Convergence Rates for Cooperative Learning Over Time-Varying Directed Graphs.39 indexed citations
8.
Leonard, Naomi Ehrich, et al.. (2016). COOPERATIVE LEARNING IN MULTI-AGENT SYSTEMS FROM INTERMITTENT MEASUREMENTS∗.11 indexed citations
9.
Olshevsky, Alex. (2014). Average Consensus in Nearly Linear Time on Fixed Graphs and Implications for Decentralized Optimization and Multi-Agent Control.. arXiv (Cornell University).2 indexed citations
Blondel, Vincent D. & Alex Olshevsky. (2012). On the Cost of Deciding Consensus. arXiv (Cornell University).2 indexed citations
15.
Yurkov, M.V., et al.. (2010). PROPOSAL FOR AN ACCELERATOR COMPLEX FOR EXTREME ULTRAVIOLET NANOLITHOGRAPHY USING KW-SCALE FEL LIGHT SOURCE.3 indexed citations
Nedić, A., Alex Olshevsky, Asuman Ozdaglar, & John N. Tsitsiklis. (2009). On Distributed Averaging Algorithms and Quantization Effects. IEEE Transactions on Automatic Control. 54(11). 2506–2517.359 indexed citations breakdown →
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.