Tyler Lu

1.8k citations
27 papers · 856 · h-index 14

Impact in

Papers in

Tyler Lu

26 papers receiving 813 citations

Peers

Tyler Lu
Comparison fields: 5 of 77
  • Management Science and Operations Research 366
  • Artificial Intelligence 418
  • Economics and Econometrics 330
  • General Decision Sciences 18
  • Computational Theory and Mathematics 122
Replace Ulle Endriss with:
Ulle Endriss Netherlands
Evangelos Markakis Greece
Nina Narodytska Australia
Mohammad Taghi Hajiaghayi United States
Shuichi Miyazaki Japan
Erik Vee United States
Dávid Pál Canada
Gagan Aggarwal United States
Michael Wooldridge United Kingdom
Vivekanand Gopalkrishnan Singapore
Tyler Lu relative to Ulle Endriss Netherlands Ulle Endriss's profile →
Citations per field
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Citations per year

Countries citing papers authored by Tyler Lu

Since Specialization
Citations

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

Fields of papers citing papers by Tyler Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Tyler Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tyler Lu Line = papers co-authored together Tyler Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011106
2
Contextual Multi-Armed Bandits
201090
3
Learning Mallows Models with Pairwise Preferences
201189
4
Impossibility Theorems for Domain Adaptation
201087
5 201570
6
Data Center Cooling using Model-predictive Control
201864
7
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning.
200852
8 201150
9 201250
10 200938
11
Effective sampling and learning for mallows models with pairwise-preference data
201434
12
Budget allocation using weakly coupled, constrained Markov decision processes
201626
13 201017
14 201516
15
Multi-winner social choice with incomplete preferences
201312
16
Non-delusional Q-learning and value-iteration
201810
17
Showing Relevant Ads via Lipschitz Context Multi-Armed Bandits
201010
18 201210
19 20087
20 20146

About Tyler Lu

Tyler Lu is a scholar working on Management Science and Operations Research, Artificial Intelligence, Economics and Econometrics, Signal Processing and Transportation, having authored 27 papers that have together received 856 indexed citations. Recurring topics across this work include Auction Theory and Applications (10 papers), Game Theory and Voting Systems (8 papers), Advanced Bandit Algorithms Research (5 papers), Data Management and Algorithms (4 papers), Transportation Planning and Optimization (4 papers), Supply Chain and Inventory Management (3 papers), Machine Learning and Algorithms (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Management Science and Operations Research (366 citations), Artificial Intelligence (418 citations), Economics and Econometrics (330 citations), General Decision Sciences (18 citations) and Computational Theory and Mathematics (122 citations). Tyler Lu has collaborated with scholars based in Canada, United States and Israel. Frequent co-authors include Craig Boutilier, Dávid Pál, Shai Ben-David, Martin Pál, Or Sheffet, Ioannis Caragiannis, Simi Haber, Ariel D. Procaccia, Alejandro López-Ortíz and Jérémy Barbay. Their work appears in journals such as Artificial Intelligence, Journal of Machine Learning Research, ACM Journal of Experimental Algorithmics, Conference on Learning Theory and Uncertainty in Artificial Intelligence.

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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