Pengkun Yang

945 total citations
19 papers, 486 citations indexed

About

Pengkun Yang is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Networks and Communications. According to data from OpenAlex, Pengkun Yang has authored 19 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Statistics and Probability and 3 papers in Computer Networks and Communications. Recurrent topics in Pengkun Yang's work include Machine Learning and Algorithms (4 papers), Bayesian Methods and Mixture Models (3 papers) and Statistical Methods and Bayesian Inference (2 papers). Pengkun Yang is often cited by papers focused on Machine Learning and Algorithms (4 papers), Bayesian Methods and Mixture Models (3 papers) and Statistical Methods and Bayesian Inference (2 papers). Pengkun Yang collaborates with scholars based in United States, China and Macao. Pengkun Yang's co-authors include Yihong Wu, Hao Feng, D. Tao, Guohan Lu, Dave Maltz, Yixin Zheng, Haitao Wu, Rui Xia, Lihua Yuan and Chuanxiong Guo and has published in prestigious journals such as IEEE Transactions on Information Theory, Pattern Recognition and The Annals of Statistics.

In The Last Decade

Pengkun Yang

18 papers receiving 467 citations

Peers

Countries citing papers authored by Pengkun Yang

Since Specialization

Citations

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

Fields of papers citing papers by Pengkun Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengkun Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Pengkun Yang. A scholar is included among the top collaborators of Pengkun Yang 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 Pengkun Yang. Pengkun Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

#	Work	Indexed citations
1	Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs 2025 ·IEEE Transactions on Information Theory ·(unknown), (unknown), Pengkun Yang	2
2	Deep Active Learning with Noise Stability 2024 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Xingjian Li, Pengkun Yang, (unknown), Xueying Zhan, Tianyang Wang, Min Xu, Chengzhong Xu	6
3	Semi-supervised transfer learning with hierarchical self-regularization 2023 ·Pattern Recognition ·Xingjian Li, Abulikemu Abuduweili, Humphrey Shi, Pengkun Yang, Dejing Dou, Haoyi Xiong, Chengzhong Xu	10
4	Age Optimal Sampling Under Unknown Delay Statistics 2023 ·IEEE Transactions on Information Theory ·Haoyue Tang, Yuchao Chen, Jintao Wang, Pengkun Yang, Leandros Tassiulas	17
5	On the best approximation by finite Gaussian mixtures 2023 ·(unknown), Yihong Wu, Pengkun Yang	0
6	Sampling for remote estimation of an Ornstein-Uhlenbeck process through channel with unknown delay statistics 2023 ·Journal of Communications and Networks ·Yuchao Chen, Haoyue Tang, Jintao Wang, Pengkun Yang, Leandros Tassiulas	1
7	Optimal estimation of high-dimensional Gaussian location mixtures 2023 ·The Annals of Statistics ·(unknown), Yihong Wu, Pengkun Yang, Harrison H. Zhou	7
8	Boosting Active Learning via Improving Test Performance 2022 ·Proceedings of the AAAI Conference on Artificial Intelligence ·(unknown), (unknown), Pengkun Yang, Guosheng Hu, Xiangrui Zeng, Siyu Huang, Chengzhong Xu, (unknown)	2
9	Layered Lossless Compression Method of Massive Fault Recording Data 2022 ·International Journal of Circuits Systems and Signal Processing ·(unknown), Pengkun Yang, (unknown), (unknown)	1
10	Polynomial Methods in Statistical Inference: Theory and Practice 2020 ·arXiv (Cornell University) ·Yihong Wu, Pengkun Yang	6
11	Utilization of text mining as a big data analysis tool for food science and nutrition 2020 ·Comprehensive Reviews in Food Science and Food Safety ·D. Tao, Pengkun Yang, Hao Feng	145
12	Optimal estimation of Gaussian mixtures via denoised method of moments 2020 ·The Annals of Statistics ·Yihong Wu, Pengkun Yang	22
13	On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective 2019 ·arXiv (Cornell University) ·Lili Su, Pengkun Yang	6
14	Chebyshev polynomials, moment matching, and optimal estimation of the unseen 2019 ·The Annals of Statistics ·Yihong Wu, Pengkun Yang	26
15	Sample complexity of the distinct elements problem 2018 ·Yihong Wu, Pengkun Yang	3
16	Minimax Rates of Entropy Estimation on Large Alphabets via Best Polynomial Approximation 2016 ·IEEE Transactions on Information Theory ·Yihong Wu, Pengkun Yang	85
17	Optimal entropy estimation on large alphabet: fundamental limits and fast algorithms 2016 ·IDEALS (University of Illinois Urbana-Champaign) ·Pengkun Yang	1
18	Optimal entropy estimation on large alphabets via best polynomial approximation 2015 ·Yihong Wu, Pengkun Yang	7
19	Per-packet load-balanced, low-latency routing for clos-based data center networks 2013 ·Jiaxin Cao, Rui Xia, Pengkun Yang, Chuanxiong Guo, Guohan Lu, Lihua Yuan, Yixin Zheng, Haitao Wu, Yongqiang Xiong, Dave Maltz	139

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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