Yingyu Liang
About
In The Last Decade
Yingyu Liang
53 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 354
- Signal Processing 145
- Information Systems 144
- Experimental and Cognitive Psychology 109
Countries citing papers authored by Yingyu Liang
This map shows the geographic impact of Yingyu Liang'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 Yingyu Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingyu Liang more than expected).
Fields of papers citing papers by Yingyu Liang
This network shows the impact of papers produced by Yingyu Liang. 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 Yingyu Liang. The network helps show where Yingyu Liang may publish in the future.
Co-authorship network of co-authors of Yingyu Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Yingyu Liang. A scholar is included among the top collaborators of Yingyu Liang 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 Yingyu Liang. Yingyu Liang 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 | 20 | |
| 3 | 1 | |
| 4 | Influence of the Integration of MMC-HVDC Station on Traditional Phase Selection Method and the Countermeasure | 1 |
| 5 | Sketching Transformed Matrices with Applications to Natural Language Processing. | 1 |
| 6 | Robust Out-of-distribution Detection via Informative Outlier Mining. | 3 |
| 7 | Non-Convex Matrix Completion and Related Problems via Strong Duality | 3 |
| 8 | Robust Attribution Regularization | 2 |
| 9 | Improving Adversarial Robustness by Data-Specific Discretization. | 4 |
| 10 | N-Gram Graph, A Novel Molecule Representation. | 2 |
| 11 | Differentially Private Clustering in High-Dimensional Euclidean Spaces | 24 |
| 12 | Scalable inuence maximization for multiple products in continuous-time diffusion networks | 16 |
| 13 | Diversity Leads to Generalization in Neural Networks. | 4 |
| 14 | Learning in indefinite proximity spaces - Recent trends | 1 |
| 15 | Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. | 4 |
| 16 | Efficient Semi-supervised and Active Learning of Disjunctions | 4 |
| 17 | Distributed k-means and k-median clustering on general communication topologies | 13 |
| 18 | Continuous-Time Influence Maximization for Multiple Items. | 3 |
| 19 | Distributed k-means and k-median Clustering on General Topologies | 12 |
| 20 | THU-IMG at TRECVID 2009 | 1 |
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.