Ranking Functions
Ranking Functions is a mathematical construct used in termination analysis to prove that a program's execution eventually halts by mapping computational states to a well-founded domain, thereby ensuring progress toward termination through strictly decreasing values.
306
Publications
22.1K
Citations
726
Authors
300
Institutions
Publications per year
2017–2026
64
306
Learning to rank using gradient descent
Chris Burges, Tal Shaked, Erin Renshaw et al. · 2005 · 2.8K citations
Novelty and diversity in information retrieval evaluation
Charles L. A. Clarke, Maheedhar Kolla, Gordon V. Cormack et al. · 2008 · 951 citations
Devi Parikh, Kristen Grauman · 2011 · 900 citations
Modeling video evolution for action recognition
Basura Fernando, Efstratios Gavves, José Oramas et al. · 2015 · 612 citations · Full text
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300
Microsoft (United States)
Redmond, United States
15 h-index
36 publications
21.5K citations
Yahoo (United States)
Sunnyvale, United States
12 h-index
51 publications
4.5K citations
University of Maryland, College Park
College Park, United States
11 h-index
22 publications
2K citations
Microsoft Research Asia (China)
Beijing, China
10 h-index
24 publications
1.9K citations
Georgia Institute of Technology
Atlanta, United States
8 h-index
11 publications
630 citations
New York University
New York, United States
7 h-index
12 publications
215 citations

Cornell University
Ithaca, United States
6 h-index
16 publications
2.5K citations

Chinese Academy of Sciences
Beijing, China
6 h-index
14 publications
986 citations
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Repository · 11 publications · 541 citations
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TKDE · 6 publications · 200 citations
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PVLDB · 4 publications · 191 citations
4
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4 publications · 120 citations
4
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LMCS · 4 publications · 92 citations
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