Xiao–Tong Yuan
About
In The Last Decade
Xiao–Tong Yuan
110 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Computer Vision and Pattern Recognition 1.4k
- Media Technology 736
- Artificial Intelligence 548
- Computational Mechanics 541
- Biomedical Engineering 494
Countries citing papers authored by Xiao–Tong Yuan
This map shows the geographic impact of Xiao–Tong Yuan'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 Xiao–Tong Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao–Tong Yuan more than expected).
Fields of papers citing papers by Xiao–Tong Yuan
This network shows the impact of papers produced by Xiao–Tong Yuan. 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 Xiao–Tong Yuan. The network helps show where Xiao–Tong Yuan may publish in the future.
Co-authorship network of co-authors of Xiao–Tong Yuan
This figure shows the co-authorship network connecting the top 25 collaborators of Xiao–Tong Yuan. A scholar is included among the top collaborators of Xiao–Tong Yuan 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 Xiao–Tong Yuan. Xiao–Tong Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | Task Similarity Aware Meta Learning: Theory-inspired Improvement on MAML | 15 |
| 7 | Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond | 1 |
| 8 | 35 | |
| 9 | Nearly Non-Expansive Bounds for Mahalanobis Hard Thresholding | 1 |
| 10 | Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning | 3 |
| 11 | Efficient Meta Learning via Minibatch Proximal Update | 14 |
| 12 | Matrix Completion with Nonuniform Sampling: Theories and Methods. | 1 |
| 13 | New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity | 4 |
| 14 | Efficient Stochastic Gradient Hard Thresholding | 7 |
| 15 | Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization. | 4 |
| 16 | Efficient k-support-norm regularized minimization via fully corrective frank-Wolfe method | 1 |
| 17 | Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization | 39 |
| 18 | 3 | |
| 19 | Forward Basis Selection for Sparse Approximation over Dictionary | 6 |
| 20 | A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems | 3 |
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.