Lihong Li

65 papers receiving 2.2k citations

Hit Papers

Parallelized Stochastic Gradient Descent201020262015202020102011200400600

Peers

Lihong Li
Comparison fields: 5 of 128
  • Artificial Intelligence 1.5k
  • Management Science and Operations Research 608
  • Computer Vision and Pattern Recognition 482
  • Computer Networks and Communications 293
  • Information Systems 269
Replace Martin Zinkevich with:
Martin Zinkevich United States
Xiang Ren United States
Daniel Golovin United States
Ran El‐Yaniv Israel
David Cohn United States
Zhendong Mao China
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Andrew L. Maas United States
Prabir Bhattacharya United States
Qiang Liu China
Lihong Li relative to Martin Zinkevich United States Martin Zinkevich's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lihong Li

Since Specialization
Citations

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

Fields of papers citing papers by Lihong Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lihong Li

This figure shows the co-authorship network connecting the top 25 collaborators of Lihong Li. A scholar is included among the top collaborators of Lihong Li 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 Lihong Li. Lihong Li 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 0
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3 1
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5 2
6 2
7
Escaping the Gravitational Pull of Softmax
4
8 29
9
Composite Task-Completion Dialogue System via Hierarchical Deep Reinforcement Learning.
6
10
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives
12
11
Active Learning with Oracle Epiphany
2
12
{Toward Minimax Off-policy Value Estimation}
24
13
PAC-inspired Option Discovery in Lifelong Reinforcement Learning
33
14
Mathematical model based on the product sales market forecast of markov forecasting and application
3
15
Open Problem: Regret Bounds for Thompson Sampling
5
16
Sample-efficient nonstationary policy evaluation for contextual bandits
10
17
An Empirical Evaluation of Thompson Samplingbreakdown →
492
18
Parallelized Stochastic Gradient Descentbreakdown →
623
19 29
20
Efficient Value-Function Approximation via Online Linear Regression.
2

About Lihong Li

Lihong Li is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 70 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (16 papers), Machine Learning and Algorithms (13 papers) and Reinforcement Learning in Robotics (13 papers). The work is most often cited by research in Management Science and Operations Research (608 citations), Artificial Intelligence (1.5k citations) and Computer Vision and Pattern Recognition (482 citations). Lihong Li has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Olivier Chapelle, Martin Zinkevich, Markus Weimer, Alex Smola, Jianfeng Gao, Michel Galley, John Langford, Michael L. Littman, Tong Zhang and Emma Brunskill. Their work appears in journals such as IEEE Access, IEEE Transactions on Biomedical Engineering and Sensors.

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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