Aravindan Vijayaraghavan

1.2k total citations
28 papers, 340 citations indexed

About

Aravindan Vijayaraghavan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Aravindan Vijayaraghavan has authored 28 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computational Theory and Mathematics, 14 papers in Artificial Intelligence and 9 papers in Computer Networks and Communications. Recurrent topics in Aravindan Vijayaraghavan's work include Complexity and Algorithms in Graphs (14 papers), Optimization and Search Problems (8 papers) and Advanced Graph Theory Research (8 papers). Aravindan Vijayaraghavan is often cited by papers focused on Complexity and Algorithms in Graphs (14 papers), Optimization and Search Problems (8 papers) and Advanced Graph Theory Research (8 papers). Aravindan Vijayaraghavan collaborates with scholars based in United States, Israel and Canada. Aravindan Vijayaraghavan's co-authors include Aditya Bhaskara, Moses Charikar, Eden Chlamtáč, Uriel Feige, Ankur Moitra, Yury Makarychev, Konstantin Makarychev, Yuan Zhou, Venkatesan Guruswami and Pranjal Awasthi and has published in prestigious journals such as Mathematical Programming, Physical review. A and ACM Transactions on Algorithms.

In The Last Decade

Aravindan Vijayaraghavan

25 papers receiving 322 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aravindan Vijayaraghavan United States 8 182 140 82 36 35 28 340
Sushant Sachdeva United States 10 154 0.8× 132 0.9× 63 0.8× 22 0.6× 9 0.3× 32 307
Morteza Monemizadeh United States 9 138 0.8× 161 1.1× 112 1.4× 56 1.6× 9 0.3× 24 303
Thorsten Theobald Germany 12 220 1.2× 75 0.5× 35 0.4× 23 0.6× 7 0.2× 42 419
Gilles Villard France 16 409 2.2× 242 1.7× 94 1.1× 20 0.6× 27 0.8× 44 605
Michael Kapralov United States 15 197 1.1× 213 1.5× 158 1.9× 59 1.6× 7 0.2× 34 462
Dima Grigoriev France 12 377 2.1× 228 1.6× 47 0.6× 19 0.5× 12 0.3× 71 564
Samuel Fiorini Belgium 14 399 2.2× 119 0.8× 127 1.5× 8 0.2× 9 0.3× 70 630
Alex Samorodnitsky Israel 17 571 3.1× 419 3.0× 199 2.4× 26 0.7× 12 0.3× 44 857
Prasad Raghavendra United States 19 689 3.8× 358 2.6× 256 3.1× 23 0.6× 19 0.5× 57 950
Hariharan Narayanan United States 11 163 0.9× 126 0.9× 69 0.8× 17 0.5× 3 0.1× 42 443

Countries citing papers authored by Aravindan Vijayaraghavan

Since Specialization
Citations

This map shows the geographic impact of Aravindan Vijayaraghavan'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 Aravindan Vijayaraghavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aravindan Vijayaraghavan more than expected).

Fields of papers citing papers by Aravindan Vijayaraghavan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aravindan Vijayaraghavan. 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 Aravindan Vijayaraghavan. The network helps show where Aravindan Vijayaraghavan may publish in the future.

Co-authorship network of co-authors of Aravindan Vijayaraghavan

This figure shows the co-authorship network connecting the top 25 collaborators of Aravindan Vijayaraghavan. A scholar is included among the top collaborators of Aravindan Vijayaraghavan 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 Aravindan Vijayaraghavan. Aravindan Vijayaraghavan 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.
Kothari, Pravesh K., et al.. (2024). Efficient Certificates of Anti-Concentration Beyond Gaussians. 970–987. 1 indexed citations
2.
Lang, Hunter, David Sontag, & Aravindan Vijayaraghavan. (2024). Theoretical Analysis of Weak-to-Strong Generalization. 46837–46880.
3.
Bhaskara, Aditya, et al.. (2020). Smoothed analysis for tensor methods in unsupervised learning. Mathematical Programming. 193(2). 549–599. 3 indexed citations
4.
Vijayaraghavan, Aravindan, et al.. (2017). Clustering stable instances of euclidean k-means. neural information processing systems. 30. 6500–6509. 6 indexed citations
5.
Chuzhoy, Julia, Yury Makarychev, Aravindan Vijayaraghavan, & Yuan Zhou. (2015). Approximation Algorithms and Hardness of the k -Route Cut Problem. ACM Transactions on Algorithms. 12(1). 1–40. 3 indexed citations
6.
Barak, Boaz, Ankur Moitra, Ryan O’Donnell, et al.. (2015). Beating the Random Assignment on Constraint Satisfaction Problems of Bounded Degree. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 15 indexed citations
7.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2014). Bilu-linial stable instances of max cut and minimum multiway cut. Symposium on Discrete Algorithms. 890–906. 8 indexed citations
8.
Bhaskara, Aditya, Moses Charikar, Ankur Moitra, & Aravindan Vijayaraghavan. (2014). Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold?. Conference on Learning Theory. 35. 1280–1282. 1 indexed citations
9.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2014). Algorithms for Semi-random Correlation Clustering.. 1 indexed citations
10.
Awasthi, Pranjal, Avrim Blum, Or Sheffet, & Aravindan Vijayaraghavan. (2014). Learning Mixtures of Ranking Models. arXiv (Cornell University). 13 indexed citations
11.
Bhaskara, Aditya, Moses Charikar, Ankur Moitra, & Aravindan Vijayaraghavan. (2014). Smoothed analysis of tensor decompositions. 594–603. 41 indexed citations
12.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2014). Constant factor approximation for balanced cut in the PIE model. 41–49. 2 indexed citations
13.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2013). Bilu-Linial Stable Instances of Max Cut. arXiv (Cornell University). 1 indexed citations
14.
Chuzhoy, Julia, Yury Makarychev, Aravindan Vijayaraghavan, & Yuan Zhou. (2012). Approximation algorithms and hardness of the k-route cut problem. Symposium on Discrete Algorithms. 12(1). 780–799. 6 indexed citations
15.
Bhaskara, Aditya, Moses Charikar, Aravindan Vijayaraghavan, Venkatesan Guruswami, & Yuan Zhou. (2012). Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph. Symposium on Discrete Algorithms. 2012. 388–405. 34 indexed citations
16.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2012). Approximation algorithms for semi-random partitioning problems. 367–384. 15 indexed citations
17.
Charikar, Moses & Aravindan Vijayaraghavan. (2012). Beyond worst-case analysis in approximation algorithms. 1 indexed citations
18.
Bhaskara, Aditya & Aravindan Vijayaraghavan. (2011). Approximating matrix p-norms. Symposium on Discrete Algorithms. 497–511. 12 indexed citations
19.
Bhaskara, Aditya & Aravindan Vijayaraghavan. (2010). Computing the Matrix p-norm. arXiv (Cornell University). 1 indexed citations
20.
Bhaskara, Aditya, Moses Charikar, Eden Chlamtáč, Uriel Feige, & Aravindan Vijayaraghavan. (2010). Detecting high log-densities. 201–210. 154 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.

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