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.
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
19952.0k citationsMichel X. Goemans, David P. Williamsonprofile →
A General Approximation Technique for Constrained Forest Problems
1995453 citationsMichel X. Goemans, David P. Williamsonprofile →
The Design of Approximation Algorithms
2011349 citationsDavid P. Williamson, David B. Shmoysprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by David P. Williamson
Since
Specialization
Citations
This map shows the geographic impact of David P. Williamson'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 David P. Williamson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David P. Williamson more than expected).
Fields of papers citing papers by David P. Williamson
This network shows the impact of papers produced by David P. Williamson. 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 David P. Williamson. The network helps show where David P. Williamson may publish in the future.
Co-authorship network of co-authors of David P. Williamson
This figure shows the co-authorship network connecting the top 25 collaborators of David P. Williamson.
A scholar is included among the top collaborators of David P. Williamson 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 David P. Williamson. David P. Williamson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Williamson, David P.. (1999). Lecture notes on approximation algorithms: Fall 1998. eCommons (Cornell University). 263(31). 16364–71.2 indexed citations
12.
Jain, Kamal, Ion Măndoiu, Vijay V. Vazirani, & David P. Williamson. (1999). A primal-dual schema based approximation algorithm for the element connectivity problem. Symposium on Discrete Algorithms. 484–489.14 indexed citations
13.
Goemans, Michel X. & David P. Williamson. (1996). Primal-Dual Approximation Algorithms for Feedback Problems. 147–161.1 indexed citations
14.
Khanna, Sanjeev, Madhu Sudan, & David P. Williamson. (1996). A Complete Characterization of the Approximability of Maximization Problems Derived from Boolean Constraint Satisfaction. Electronic colloquium on computational complexity. 3.1 indexed citations
15.
Goemans, Michel X. & David P. Williamson. (1996). The primal-dual method for approximation algorithms and its application to network design problems. 144–191.174 indexed citations
16.
Trevisan, Luca, Gregory B. Sorkin, Madhu Sudan, & David P. Williamson. (1996). Gadgets, Approximation, and Linear Programming (extended abstract).. 617–626.6 indexed citations
Goemans, Michel X. & David P. Williamson. (1993). A new \frac34-approximation algorithm for MAX SAT.. 57(38). 313–321.8 indexed citations
20.
Goemans, Michel X. & David P. Williamson. (1992). A general approximation technique for constrained forest problems. Symposium on Discrete Algorithms. 307–316.37 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.