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.
An analysis of temporal-difference learning with function approximation
1997717 citationsJohn N. Tsitsiklis, Benjamin Van Royprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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Countries citing papers authored by Benjamin Van Roy
Since
Specialization
Citations
This map shows the geographic impact of Benjamin Van Roy'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 Benjamin Van Roy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Van Roy more than expected).
Fields of papers citing papers by Benjamin Van Roy
This network shows the impact of papers produced by Benjamin Van Roy. 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 Benjamin Van Roy. The network helps show where Benjamin Van Roy may publish in the future.
Co-authorship network of co-authors of Benjamin Van Roy
This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Van Roy.
A scholar is included among the top collaborators of Benjamin Van Roy 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 Benjamin Van Roy. Benjamin Van Roy is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wen, Zheng, et al.. (2020). On Efficiency in Hierarchical Reinforcement Learning. Neural Information Processing Systems. 33. 6708–6718.9 indexed citations
4.
Ma, Tengyu, et al.. (2019). On the Performance of Thompson Sampling on Logistic Bandits. Conference on Learning Theory. 1158–1160.1 indexed citations
5.
Osband, Ian, Benjamin Van Roy, Daniel Russo, & Zheng Wen. (2019). Deep Exploration via Randomized Value Functions. Journal of Machine Learning Research. 20(124). 1–62.47 indexed citations
6.
Osband, Ian, et al.. (2018). Scalable Coordinated Exploration in Concurrent Reinforcement Learning. arXiv (Cornell University). 31. 4219–4227.3 indexed citations
7.
Lu, Xiuyuan & Benjamin Van Roy. (2017). Ensemble Sampling. Neural Information Processing Systems. 30. 3258–3266.4 indexed citations
8.
Osband, Ian & Benjamin Van Roy. (2014). Model-based Reinforcement Learning and the Eluder Dimension. arXiv (Cornell University). 27. 1466–1474.7 indexed citations
9.
Roy, Benjamin Van, et al.. (2013). Eluder Dimension and the Sample Complexity of Optimistic Exploration. Neural Information Processing Systems. 26. 2256–2264.14 indexed citations
10.
Javanmard, Adel, et al.. (2012). Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems. Neural Information Processing Systems. 25. 2636–2644.9 indexed citations
11.
Roy, Benjamin Van, et al.. (2009). Directed Regression. Neural Information Processing Systems. 22. 889–897.11 indexed citations
12.
Weintraub, Gabriel Y., et al.. (2005). Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games. Neural Information Processing Systems. 18. 1489–1496.64 indexed citations
13.
Diaconis, Persi, et al.. (2004). Solitaire: Man Versus Machine. Neural Information Processing Systems. 17. 1553–1560.17 indexed citations
14.
Moallemi, Ciamac C. & Benjamin Van Roy. (2003). Distributed Optimization in Adaptive Networks. Neural Information Processing Systems. 16. 887–894.28 indexed citations
15.
Roy, Benjamin Van, et al.. (2002). Approximate Linear Programming for Average-Cost Dynamic Programming. Neural Information Processing Systems. 15. 1619–1626.12 indexed citations
16.
Rusmevichientong, Paat & Benjamin Van Roy. (1999). An Analysis of Turbo Decoding with Gaussian Densities. Neural Information Processing Systems. 12. 575–581.11 indexed citations
17.
Tsitsiklis, John N. & Benjamin Van Roy. (1996). Analysis of temporal-difference learning with function approximation. Neural Information Processing Systems. 1075–1081.14 indexed citations
18.
Tsitsiklis, John N. & Benjamin Van Roy. (1996). Approximate Solutions to Optimal Stopping Problems. Neural Information Processing Systems. 9. 1082–1088.3 indexed citations
19.
Tsitsiklis, John N. & Benjamin Van Roy. (1996). Analysis of Temporal-Diffference Learning with Function Approximation. Neural Information Processing Systems. 9. 1075–1081.55 indexed citations
20.
Roy, Benjamin Van & John N. Tsitsiklis. (1995). Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions. Neural Information Processing Systems. 8. 1045–1051.7 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.