Mingrui Liu
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- Stochastic Gradient Optimization Techniques 5
- Privacy-Preserving Technologies in Data 4
- Machine Learning and Algorithms 2
- Machine Learning and ELM 2
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- Sparse and Compressive Sensing Techniques 4
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- Ecology and Vegetation Dynamics Studies 4
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- Pasture and Agricultural Systems 3
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- Speech and Audio Processing 2
- Co-authors
- Tianbao YangQihang LinGuoao LiPaul H. FallgrenLiang ChenYe YaoSong JinJie Hou
- Journals
- Chemosphere (1 paper)The Journal of the Acoustical Society of America (1 paper)The Journal of Organic Chemistry (1 paper)
- Partner nations
- ChinaUnited StatesBelgium
In The Last Decade
Mingrui Liu
23 papers receiving 147 citations
Peers
Comparison fields: 5 of 77
- Environmental Chemistry 29
- Numerical Analysis 10
- Artificial Intelligence 52
- Health, Toxicology and Mutagenesis 21
- Computational Mechanics 24
Countries citing papers authored by Mingrui Liu
This map shows the geographic impact of Mingrui Liu'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 Mingrui Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingrui Liu more than expected).
Fields of papers citing papers by Mingrui Liu
This network shows the impact of papers produced by Mingrui Liu. 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 Mingrui Liu. The network helps show where Mingrui Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mingrui Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 1 | |
| 8 | 2022 | 1 | |
| 9 | 2022 | 0 | |
| 10 | Generalization Guarantee of SGD for Pairwise Learning | 2021 | 9 |
| 11 | 2021 | 42 | |
| 12 | 2021 | 1 | |
| 13 | Stochastic AUC Maximization with Deep Neural Networks | 2020 | 2 |
| 14 | Improved Schemes for Episodic Memory-based Lifelong Learning | 2020 | 4 |
| 15 | Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks | 2020 | 1 |
| 16 | 2020 | 9 | |
| 17 | Attacking Lifelong Learning Models with Gradient Reversion | 2019 | 2 |
| 18 | 2019 | 5 | |
| 19 | Faster online learning of optimal threshold for consistent F-measure optimization | 2018 | 2 |
| 20 | No More Fixed Penalty Parameter in ADMM: Faster Convergence with New Adaptive Penalization | 2017 | 0 |
About Mingrui Liu
Mingrui Liu is a scholar working on Forestry, Artificial Intelligence and Nature and Landscape Conservation, having authored 27 papers that have together received 149 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (5 papers), Sparse and Compressive Sensing Techniques (4 papers), Privacy-Preserving Technologies in Data (4 papers), Ecology and Vegetation Dynamics Studies (4 papers), Pasture and Agricultural Systems (3 papers), Speech and Audio Processing (2 papers), Machine Learning and Algorithms (2 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Environmental Chemistry (29 citations), Numerical Analysis (10 citations) and Artificial Intelligence (52 citations). Mingrui Liu has collaborated with scholars based in China, United States and Belgium. Frequent co-authors include Tianbao Yang, Qihang Lin, Guoao Li, Paul H. Fallgren, Liang Chen, Ye Yao, Song Jin, Jie Hou, Yiming Ying and Yunwen Lei. Their work appears in journals such as Chemosphere, The Journal of the Acoustical Society of America and The Journal of Organic Chemistry.
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.