Scholar
Jingfeng Wu
Google Scholar ID: z-KILD8AAAAJ
University of California, Berkeley
deep learning theory
machine learning
optimization
statistical learning theory
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Citations & Impact
All-time
Citations
1,384
H-index
20
i10-index
25
Publications
20
Co-authors
52
list available
Publications
19 items
Principal Component Regression Dominates all Monotone Spectral Filters for Linear Regression
2026
Cited
0
CoCoScale: Leveraging Layer-wise Scaling to Unlock the Potential of Online LLM Serving
2026
Cited
0
Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
2026
Cited
0
Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling
2025
Cited
0
BanaServe: Unified KV Cache and Dynamic Module Migration for Balancing Disaggregated LLM Serving in AI Infrastructure
2025
Cited
0
Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization
2025
Cited
0
On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models
2025
Cited
0
Unlock the Potential of Fine-grained LLM Serving via Dynamic Module Scaling
2025
Cited
0
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Co-authors
18 total
Vladimir Braverman
Professor of Computer Science, Johns Hopkins University; Google Research; Adjunct Professor, Rice U.
Difan Zou
The University of Hong Kong
Sham M Kakade
Harvard University
Quanquan Gu
Associate Professor of Computer Science, UCLA
Peter Bartlett
Professor, EECS and Statistics, UC Berkeley
Zhanxing Zhu
Associate Professor, ECS, University of Southampton
Xin Jin
Peking University
Zhuolong Yu
Microsoft
