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Fangcheng Fu
- Author ID
- u19083
- ORCID
-
-
- Links
-
(found by gpt-5.6-luna on jul 24 2026)
- Most Frequent Institution
- Peking University
- Pagerank
- 0.099357671
- Overall Rank
- 700 | 96.77%
- Paper Count
- 13
Affiliation Timeline
Incoming Non-self Citations Over Time
Total yearly non-self incoming citations across all papers by this author.
Publications by Paper Pagerank
Showing 13 of 13 publications.
| Rank |
Title |
Year |
Venue |
Pagerank |
| 2,007 |
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning |
2021 |
SIGMOD |
9.198944e-05 |
| 3,311 |
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data |
2022 |
SIGMOD |
7.4392547e-05 |
| 3,872 |
SketchML: Accelerating Distributed Machine Learning with Data Sketches |
2018 |
SIGMOD |
6.9540368e-05 |
| 4,498 |
PQCache: Product Quantization-based KVCache for Long Context LLM Inference |
2025 |
SIGMOD |
6.5762771e-05 |
| 5,723 |
An Experimental Evaluation of Large Scale GBDT Systems |
2019 |
VLDB |
6.0178515e-05 |
| 8,197 |
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent |
2023 |
VLDB |
5.3794747e-05 |
| 9,846 |
DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions |
2018 |
SIGMOD |
5.121318e-05 |
| 10,042 |
MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training |
2025 |
SIGMOD |
5.0921006e-05 |
| 10,342 |
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates |
2022 |
VLDB |
5.0167904e-05 |
| 10,577 |
Hydraulis: Balancing Large Transformer Model Training via Co-designing Parallel Strategies and Data Assignment |
2026 |
SIGMOD |
4.9793485e-05 |
| 11,189 |
Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization |
2025 |
SIGMOD |
4.9793485e-05 |
| 11,282 |
LobRA: Multi-tenant Fine-tuning over Heterogeneous Data |
2025 |
VLDB |
4.9793485e-05 |
| 11,324 |
PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning |
2025 |
VLDB |
4.9793485e-05 |
Frequent Co-authors
Co-authored at least 5 papers.