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.
Countries citing papers authored by Satinder Singh
Since
Specialization
Citations
This map shows the geographic impact of Satinder Singh'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 Satinder Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satinder Singh more than expected).
This network shows the impact of papers produced by Satinder Singh. 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 Satinder Singh. The network helps show where Satinder Singh may publish in the future.
Co-authorship network of co-authors of Satinder Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Satinder Singh.
A scholar is included among the top collaborators of Satinder Singh 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 Satinder Singh. Satinder Singh is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Oh, Junhyuk, Matteo Hessel, Wojciech Marian Czarnecki, et al.. (2020). Discovering Reinforcement Learning Algorithms. Neural Information Processing Systems. 33. 1060–1070.1 indexed citations
3.
Zahavy, Tom, Zhongwen Xu, Vivek Veeriah, et al.. (2020). A Self-Tuning Actor-Critic Algorithm. Neural Information Processing Systems. 33. 20913–20924.2 indexed citations
4.
Guo, Xiaoxiao, Tim Klinger, Joseph P. Bigus, et al.. (2017). Learning to Query, Reason, and Answer Questions On Ambiguous Texts. International Conference on Learning Representations.7 indexed citations
5.
Jiang, Nan, Satinder Singh, & Ambuj Tewari. (2016). On structural properties of MDPs that bound loss due to shallow planning. International Joint Conference on Artificial Intelligence. 1640–1647.2 indexed citations
Sorg, Jonathan, Richard L. Lewis, & Satinder Singh. (2010). Reward Design via Online Gradient Ascent. Neural Information Processing Systems. 23. 2190–2198.38 indexed citations
10.
Sorg, Jonathan, Satinder Singh, & Richard L. Lewis. (2010). Variance-based rewards for approximate Bayesian reinforcement learning. Uncertainty in Artificial Intelligence. 564–571.15 indexed citations
11.
Precup, Doina, et al.. (2005). Off-policy Learning with Options and Recognizers. Neural Information Processing Systems. 18. 1097–1104.5 indexed citations
12.
Isbell, Charles L., et al.. (2000). Cobot in LambdaMOO: A Social Statistics Agent. National Conference on Artificial Intelligence. 36–41.41 indexed citations
13.
Kearns, Michael & Satinder Singh. (2000). Bias-Variance Error Bounds for Temporal Difference Updates. Conference on Learning Theory. 142–147.27 indexed citations
14.
Precup, Doina, Richard S. Sutton, & Satinder Singh. (2000). Eligibility Traces for Off-Policy Policy Evaluation. Scholarworks (University of Massachusetts Amherst). 759–766.172 indexed citations
Kearns, Michael & Satinder Singh. (1998). Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms. Neural Information Processing Systems. 11. 996–1002.107 indexed citations
17.
Singh, Satinder, Tommi Jaakkola, & Michael I. Jordan. (1994). Reinforcement Learning with Soft State Aggregation. Neural Information Processing Systems. 7. 361–368.149 indexed citations
18.
Singh, Satinder. (1994). Reinforcement learning algorithms for average-payoff markovian decision processes. National Conference on Artificial Intelligence. 700–705.52 indexed citations
19.
Singh, Satinder, Andrew G. Barto, Roderic A. Grupen, & Christopher I. Connolly. (1993). Robust Reinforcement Learning in Motion Planning. ScholarWorks@UMassAmherst (University of Massachusetts Amherst). 6. 655–662.30 indexed citations
20.
Singh, Satinder. (1991). The Efficient Learning of Multiple Task Sequences. Neural Information Processing Systems. 4. 251–258.16 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.