Jingfeng Wu
Scholar

Jingfeng Wu

Google Scholar ID: z-KILD8AAAAJ
University of California, Berkeley
deep learning theorymachine learningoptimizationstatistical learning theory
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Citations & Impact
All-time
Citations
1,348
 
H-index
20
 
i10-index
25
 
Publications
20
 
Co-authors
52
list available
Contact
No contact links provided.
Publications
16 items
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
Cloud Native System for LLM Inference Serving
2025
Cited
0
A Simplified Analysis of SGD for Linear Regression with Weight Averaging
2025
Cited
0
Improved Scaling Laws in Linear Regression via Data Reuse
2025
Cited
0
Resume (English only)
Co-authors
52 total
Vladimir Braverman
Vladimir Braverman
Professor of Computer Science, Johns Hopkins University; Google Research; Adjunct Professor, Rice U.
Difan Zou
Difan Zou
The University of Hong Kong
Sham M Kakade
Sham M Kakade
Harvard University
Quanquan Gu
Quanquan Gu
Associate Professor of Computer Science, UCLA
Peter Bartlett
Peter Bartlett
Professor, EECS and Statistics, UC Berkeley
Zhanxing Zhu
Zhanxing Zhu
Associate Professor, ECS, University of Southampton
Co-author 7
Co-author 7
Xin Jin
Xin Jin
Peking University