Cho‐Jui Hsieh
About
In The Last Decade
Cho‐Jui Hsieh
164 papers receiving 9.9k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Artificial Intelligence 6.3k
- Computer Vision and Pattern Recognition 3.6k
- Information Systems 1.2k
- Signal Processing 1.1k
- Computational Mechanics 997
Countries citing papers authored by Cho‐Jui Hsieh
This map shows the geographic impact of Cho‐Jui Hsieh'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 Cho‐Jui Hsieh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cho‐Jui Hsieh more than expected).
Fields of papers citing papers by Cho‐Jui Hsieh
This network shows the impact of papers produced by Cho‐Jui Hsieh. 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 Cho‐Jui Hsieh. The network helps show where Cho‐Jui Hsieh may publish in the future.
Co-authorship network of co-authors of Cho‐Jui Hsieh
This figure shows the co-authorship network connecting the top 25 collaborators of Cho‐Jui Hsieh. A scholar is included among the top collaborators of Cho‐Jui Hsieh 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 Cho‐Jui Hsieh. Cho‐Jui Hsieh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | Fast Certified Robust Training via Better Initialization and Shorter Warmup. | 2 |
| 9 | DRONE: Data-aware Low-rank Compression for Large NLP Models | 14 |
| 10 | 2 | |
| 11 | 30 | |
| 12 | Provable, Scalable and Automatic Perturbation Analysis on General Computational Graphs | 0 |
| 13 | Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data | 1 |
| 14 | The Limitations of Adversarial Training and the Blind-Spot Attack | 11 |
| 15 | ImageNet Training by CPU: AlexNet in 11 Minutes and ResNet-50 in 48 Minutes | 0 |
| 16 | A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order | 19 |
| 17 | Sparse Linear Programming via primal and dual augmented coordinate descent | 10 |
| 18 | Nuclear Norm Minimization via Active Subspace Selection | 61 |
| 19 | 2 | |
| 20 | A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification | 130 |
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.