Kaiyi Ji

606 total citations
21 papers, 152 citations indexed

About

Kaiyi Ji is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Networks and Communications. According to data from OpenAlex, Kaiyi Ji has authored 21 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 10 papers in Computational Mechanics and 6 papers in Computer Networks and Communications. Recurrent topics in Kaiyi Ji's work include Sparse and Compressive Sensing Techniques (10 papers), Stochastic Gradient Optimization Techniques (9 papers) and Caching and Content Delivery (6 papers). Kaiyi Ji is often cited by papers focused on Sparse and Compressive Sensing Techniques (10 papers), Stochastic Gradient Optimization Techniques (9 papers) and Caching and Content Delivery (6 papers). Kaiyi Ji collaborates with scholars based in United States, Hong Kong and Canada. Kaiyi Ji's co-authors include Yingbin Liang, Yi Zhou, Jian Tan, Vahid Tarokh, Yan Zhang, Ness B. Shroff, Michael M. Zavlanos, Zhe Wang, Junjie Yang and Zhe Wang and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Information Theory and Automatica.

In The Last Decade

Kaiyi Ji

21 papers receiving 148 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kaiyi Ji United States	8	87	71	35	24	18	21	152
Aolin Xu United States	7	82 0.9×	39 0.5×	31 0.9×	11 0.5×	4 0.2×	17	157
Dima Kuzmin United States	5	73 0.8×	13 0.2×	26 0.7×	31 1.3×	4 0.2×	6	104
Dylan J. Foster United States	6	54 0.6×	13 0.2×	24 0.7×	33 1.4×	3 0.2×	20	89
Yinliang Yue China	9	109 1.3×	146 2.1×	9 0.3×	12 0.5×	100 5.6×	35	255
Farbod Roosta-Khorasani United States	3	69 0.8×	14 0.2×	48 1.4×	7 0.3×	8 0.4×	6	113
Yancheng Yuan Hong Kong	5	59 0.7×	9 0.1×	24 0.7×	13 0.5×	50 2.8×	20	131
J. A. Herdman United Kingdom	9	20 0.2×	197 2.8×	15 0.4×	7 0.3×	52 2.9×	17	261
Can Karakus United States	6	82 0.9×	74 1.0×	26 0.7×	2 0.1×	8 0.4×	12	137
Kevin Scaman France	5	57 0.7×	11 0.2×	13 0.4×	5 0.2×	6 0.3×	9	105
Duy Nhat Phan France	8	46 0.5×	19 0.3×	71 2.0×	17 0.7×	2 0.1×	17	122

Countries citing papers authored by Kaiyi Ji

Since Specialization

Citations

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

Fields of papers citing papers by Kaiyi Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaiyi Ji

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Zhou, Yi, et al.. (2024). Boosting One-Point Derivative-Free Online Optimization via Residual Feedback. IEEE Transactions on Automatic Control. 69(9). 6309–6316. 2 indexed citations

Ji, Kaiyi & Lei Ying. (2023). Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach. 131–140. 3 indexed citations

Ji, Kaiyi, Junjie Yang, & Yingbin Liang. (2021). Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning. 5 indexed citations

Zhang, Yan, Yi Zhou, Kaiyi Ji, & Michael M. Zavlanos. (2021). A new one-point residual-feedback oracle for black-box learning and control. Automatica. 136. 110006–110006. 23 indexed citations

Ji, Kaiyi, Yi Zhou, & Yingbin Liang. (2021). Understanding Estimation and Generalization Error of Generative Adversarial Networks. IEEE Transactions on Information Theory. 67(5). 3114–3129. 8 indexed citations

Ji, Kaiyi, Junjie Yang, & Yingbin Liang. (2020). Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms.. arXiv (Cornell University). 4 indexed citations

Ji, Kaiyi, et al.. (2020). Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 4036–4043. 10 indexed citations

Xu, Tengyu, Yi Zhou, Kaiyi Ji, & Yingbin Liang. (2020). When will gradient methods converge to max‐margin classifier under ReLU models?. Stat. 10(1). 2 indexed citations

Ji, Kaiyi, Jian Tan, Jinfeng Xu, & Yuejie Chi. (2020). Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion. 1–5. 2 indexed citations

10.

Zhou, Yi, Zhe Wang, Kaiyi Ji, Yingbin Liang, & Vahid Tarokh. (2020). Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization. 1445–1451. 4 indexed citations

11.

Ji, Kaiyi, Jian Tan, Jinfeng Xu, & Yuejie Chi. (2020). Learning Latent Features With Pairwise Penalties in Low-Rank Matrix Completion. IEEE Transactions on Signal Processing. 68. 4210–4225. 1 indexed citations

12.

Wang, Zhe, Kaiyi Ji, Yi Zhou, Yingbin Liang, & Vahid Tarokh. (2019). SpiderBoost and Momentum: Faster Variance Reduction Algorithms. Neural Information Processing Systems. 32. 2403–2413. 23 indexed citations

13.

Tan, Jian, et al.. (2019). On Resource Pooling and Separation for LRU Caching. ACM SIGMETRICS Performance Evaluation Review. 46(1). 27–27. 1 indexed citations

14.

Xu, Tengyu, Yi Zhou, Kaiyi Ji, & Yingbin Liang. (2018). Convergence of SGD in Learning ReLU Models with Separable Data.. arXiv (Cornell University). 2 indexed citations

15.

Tan, Jian, et al.. (2018). On Resource Pooling and Separation for LRU Caching. ACM SIGMETRICS Performance Evaluation Review. 46(1). 27–27. 1 indexed citations

16.

Wang, Zhe, Kaiyi Ji, Yi Zhou, Yingbin Liang, & Vahid Tarokh. (2018). SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization.. 13 indexed citations

17.

Ji, Kaiyi, et al.. (2018). LRU Caching with Dependent Competing Requests. 459–467. 9 indexed citations

18.

Tan, Jian, et al.. (2018). On Resource Pooling and Separation for LRU Caching. 27–27. 15 indexed citations

19.

Tan, Ming Jen, et al.. (2018). On Resource Pooling and Separation for LRU Caching. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 2(1). 1–31. 6 indexed citations

20.

Ji, Kaiyi, et al.. (2018). Asymptotic Miss Ratio of LRU Caching with Consistent Hashing. 450–458. 12 indexed citations

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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