Zhaoran Wang

2.0k citations
53 papers · 615 indexed · h-index 15
Topics
Sparse and Compressive Sensing Techniques (12 papers)Reinforcement Learning in Robotics (11 papers)Advanced Bandit Algorithms Research (11 papers)
Partner nations
United StatesChinaCanada

In The Last Decade

Zhaoran Wang

49 papers receiving 590 citations

Peers

Zhaoran Wang
Comparison fields: 5 of 99
  • Computational Mechanics 208
  • Artificial Intelligence 197
  • Computational Theory and Mathematics 109
  • Management Science and Operations Research 76
  • Numerical Analysis 72
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Citations per field
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Countries citing papers authored by Zhaoran Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zhaoran Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaoran Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhaoran Wang. A scholar is included among the top collaborators of Zhaoran Wang 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 Zhaoran Wang. Zhaoran Wang 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
2 4
3 4
4 2
5 10
6 29
7 31
8 5
9
Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
3
10 18
11
Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case
2
12
Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations.
2
13
Dynamic regret of policy optimization in non-stationary environments
3
14
Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations
3
15
Statistical-Computational Tradeoff in Single Index Models
1
16
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
17
17
Neural proximal/trust region policy optimization attains globally optimal policy
23
18
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding
3
19
Agnostic estimation for misspecified phase retrieval models
5
20
Sparse nonlinear regression: parameter estimation under nonconvexity
14

About Zhaoran Wang

Zhaoran Wang is a scholar working on Computational Mathematics, Management Science and Operations Research and Statistics and Probability, having authored 53 papers that have together received 615 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (12 papers), Reinforcement Learning in Robotics (11 papers) and Advanced Bandit Algorithms Research (11 papers). The work is most often cited by research in Computational Mathematics (27 citations), Numerical Analysis (72 citations) and Computational Mechanics (208 citations). Zhaoran Wang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Han Liu, Zhuoran Yang, Xiaoming Yuan, Tuo Zhao, Mingyi Hong, Maureen Boost, Pauline Cho, Han Liu, Kean Ming Tan and Michael I. Jordan. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and Management Science.

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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