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.
This map shows the geographic impact of Eli Upfal'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 Eli Upfal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eli Upfal more than expected).
This network shows the impact of papers produced by Eli Upfal. 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 Eli Upfal. The network helps show where Eli Upfal may publish in the future.
Co-authorship network of co-authors of Eli Upfal
This figure shows the co-authorship network connecting the top 25 collaborators of Eli Upfal.
A scholar is included among the top collaborators of Eli Upfal 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 Eli Upfal. Eli Upfal is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Park, Andrew, et al.. (2021). Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees. International Conference on Artificial Intelligence and Statistics. 3196–3204.2 indexed citations
2.
Lysyanskaya, Anna, et al.. (2018). Practical and Provably Secure Onion Routing.. International Colloquium on Automata, Languages and Programming.1 indexed citations
3.
Binnig, Carsten, Lorenzo De Stefani, Tim Kraska, et al.. (2017). Toward Sustainable Insights, or Why Polygamy is Bad for You.. Conference on Innovative Data Systems Research.17 indexed citations
Slivkins, Aleksandrs & Eli Upfal. (2008). Adapting to a Changing Environment: the Brownian Restless Bandits.. Conference on Learning Theory. 343–354.44 indexed citations
7.
Chakrabarti, Deepayan, Ravi Kumar, Filip Radlinski, & Eli Upfal. (2008). Mortal Multi-Armed Bandits. Neural Information Processing Systems. 21. 273–280.56 indexed citations
8.
Katriel, Irit, Meinolf Sellmann, Eli Upfal, & Pascal Van Hentenryck. (2007). Propagating knapsack constraints in sublinear time. National Conference on Artificial Intelligence. 231–236.4 indexed citations
Ciaramita, Massimiliano, Mark Johnson, Steven A. Sloman, & Eli Upfal. (2005). Hierarchical Preferences in a Broad-Coverage Lexical Taxonomy. eScholarship (California Digital Library). 27(27).3 indexed citations
Hauskrecht, Miloš, Gopal Pandurangan, & Eli Upfal. (1999). Computing Near Optimal Strategies for Stochastic Investment Planning Problems. International Joint Conference on Artificial Intelligence. 1310–1315.1 indexed citations
13.
Broder, Andrei, Alan Frieze, & Eli Upfal. (1997). Static and Dynamic Path Selection on Expander Graphs: A Random Walk Approach (Preliminary Version).. 531–539.2 indexed citations
Feige, Uriel, David Peleg, Prabhakar Raghavan, & Eli Upfal. (1990). Computing with Unreliable Information (Preliminary Version). 128–137.1 indexed citations
Karlin, Anna R. & Eli Upfal. (1986). Parallel Hashing-An Efficient Implementation of Shared Memory (Preliminary Version). 160–168.1 indexed citations
19.
Upfal, Eli. (1984). A Probabilistic Relation between Desirable and Feasible Models of Parallel Computation (A Preliminary Version). 258–265.1 indexed citations
20.
Upfal, Eli & Avi Wigderson. (1984). How to Share Memory in a Distributed System (A Preliminary Version). 171–180.1 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.