Countries citing papers authored by Silvio Lattanzi
Since
Specialization
Citations
This map shows the geographic impact of Silvio Lattanzi'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 Silvio Lattanzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvio Lattanzi more than expected).
This network shows the impact of papers produced by Silvio Lattanzi. 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 Silvio Lattanzi. The network helps show where Silvio Lattanzi may publish in the future.
Co-authorship network of co-authors of Silvio Lattanzi
This figure shows the co-authorship network connecting the top 25 collaborators of Silvio Lattanzi.
A scholar is included among the top collaborators of Silvio Lattanzi 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 Silvio Lattanzi. Silvio Lattanzi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cohen-Addad, Vincent, et al.. (2021). Parallel and Efficient Hierarchical k-Median Clustering. Neural Information Processing Systems. 34.1 indexed citations
4.
Lattanzi, Silvio, et al.. (2021). Robust Online Correlation Clustering. Neural Information Processing Systems. 34.1 indexed citations
5.
Chierichetti, Flavio, et al.. (2021). Online Facility Location with Multiple Advice. IRIS Research product catalog (Sapienza University of Rome). 34.1 indexed citations
6.
Bhaskara, Aditya, Amin Karbasi, Silvio Lattanzi, & Morteza Zadimoghaddam. (2020). Online MAP Inference of Determinantal Point Processes. Neural Information Processing Systems. 33. 3419–3429.
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
8.
Lattanzi, Silvio & Christian Sohler. (2019). A Better k-means++ Algorithm via Local Search. International Conference on Machine Learning. 3662–3671.7 indexed citations
9.
Ghaffari, Mohsen, Silvio Lattanzi, & Slobodan Mitrović. (2019). Improved Parallel Algorithms for Density-Based Network Clustering. International Conference on Machine Learning. 2201–2210.8 indexed citations
10.
Bachem, Olivier, Mario Lučić, & Silvio Lattanzi. (2018). One-shot Coresets: The Case of k-Clustering. International Conference on Artificial Intelligence and Statistics. 784–792.6 indexed citations
11.
Vassilvitskii, Sergei & Silvio Lattanzi. (2017). Consistent k-Clustering. International Conference on Machine Learning. 1975–1984.3 indexed citations
12.
Bateni, MohammadHossein, Soheil Behnezhad, Mahsa Derakhshan, et al.. (2017). Affinity Clustering: Hierarchical Clustering at Scale. neural information processing systems. 30. 6864–6874.33 indexed citations
13.
Anagnostopoulos, Aris, Jakub Łącki, Silvio Lattanzi, Stefano Leonardi, & Mohammad Mahdian. (2016). Community Detection on Evolving Graphs. IRIS Research product catalog (Sapienza University of Rome). 29. 3522–3530.5 indexed citations
Zhu, Zeyuan Allen, Silvio Lattanzi, & Vahab Mirrokni. (2013). A Local Algorithm for Finding Well-Connected Clusters. arXiv (Cornell University). 396–404.14 indexed citations
17.
Alvisi, Lorenzo, Allen Clement, Alessandro Epasto, Silvio Lattanzi, & Alessandro Panconesi. (2013). SoK: The Evolution of Sybil Defense via Social Networks. IRIS Research product catalog (Sapienza University of Rome). 382–396.96 indexed citations
Kumar, Ravi, Silvio Lattanzi, Sergei Vassilvitskii, & Andrea Vattani. (2011). Hiring a secretary from a poset. 39–48.13 indexed citations
20.
Lattanzi, Silvio, Benjamin Moseley, Siddharth Suri, & Sergei Vassilvitskii. (2011). Filtering. 85–94.116 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.