Adith Swaminathan

1.9k citations
22 papers · 756 indexed · 1 hit paper · h-index 11
Topics
Advanced Bandit Algorithms Research (11 papers)Machine Learning and Algorithms (7 papers)Optimization and Search Problems (5 papers)
Journals
Journal of Machine Learning ResearchAI MagazinearXiv (Cornell University)

In The Last Decade

Adith Swaminathan

22 papers receiving 716 citations

Hit Papers

Unbiased Learning-to-Rank with Biased Feedback2017202620202023201750100150200250

Peers

Adith Swaminathan
Comparison fields: 5 of 59
  • Artificial Intelligence 466
  • Information Systems 382
  • Management Science and Operations Research 334
  • Computer Vision and Pattern Recognition 84
  • Computer Networks and Communications 81
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Citations per field
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Citations per year

Countries citing papers authored by Adith Swaminathan

Since Specialization
Citations

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

Fields of papers citing papers by Adith Swaminathan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adith Swaminathan

This figure shows the co-authorship network connecting the top 25 collaborators of Adith Swaminathan. A scholar is included among the top collaborators of Adith Swaminathan 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 Adith Swaminathan. Adith Swaminathan 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
#WorkIndexed citations
1 7
2
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration
6
3 42
4 2
5
Customizing Scripted Bots: Sample Efficient Imitation Learning for Human-like Behavior in Minecraft
2
6
Off-Policy Policy Gradient with State Distribution Correction
4
7 1
8 3
9
Deep Learning with Logged Bandit Feedback
27
10 6
11 28
12
Unbiased Learning-to-Rank with Biased Feedbackbreakdown →
252
13 27
14 66
15 9
16
The self-normalized estimator for counterfactual learning
89
17
Batch learning from logged bandit feedback through counterfactual risk minimization
73
18 1
19 43
20 36

About Adith Swaminathan

Adith Swaminathan is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computer Science Applications, having authored 22 papers that have together received 756 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (11 papers), Machine Learning and Algorithms (7 papers) and Optimization and Search Problems (5 papers). The work is most often cited by research in Management Science and Operations Research (334 citations), Information Systems (382 citations) and Computer Science Applications (80 citations). Adith Swaminathan has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Thorsten Joachims, Tobias Schnabel, Ashudeep Singh, Lin Ma, Bailu Ding, Sudipto Das, Maarten de Rijke, Alekh Agarwal, Emma Brunskill and Peter I. Frazier. Their work appears in journals such as Journal of Machine Learning Research, AI Magazine and arXiv (Cornell University).

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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