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Yu Zhu

6 papers hereh-index 230 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author3

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.AR4
  • cs.DC2
same name
  • Yu Zhu — 15 papers, h 14
  • Yu Zhu — 10 papers, h 10
  • Yu Zhu — 9 papers, h 6
  • Yu Zhu — 8 papers, h 17
  • Yu Zhu — 8 papers, h 2
  • Yu Zhu — 6 papers, h 15

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedEfficient Tabular Data Preprocessing of ML Pipelines

1 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing cs.ARShow all

4 papers · 1 filter

cs.AR2025

An RDMA-First Object Storage System with SmartNIC Offload

Yu Zhu, Aditya Dhakal, Pedro Bruel +4

AI training and inference impose sustained, fine-grain I/O that stresses host-mediated, TCP-based storage paths. Motivated by kernel-bypass networking and user-space storage stacks…

cs.AR2025★ 1 cited

RoCE BALBOA: Service-enhanced Data Center RDMA for SmartNICs

Maximilian Jakob Heer, Benjamin Ramhorst, Yu Zhu +4

Data-intensive applications in data centers, especially machine learning (ML), have made the network a bottleneck, which in turn has motivated the development of more efficient net…

cs.AR2025

Accelerating Recommender Model ETL with a Streaming FPGA-GPU Dataflow

Yu Zhu, Wenqi Jiang, Piyumi Jasin Pathiranage +2

The real-time performance of recommender models depends on the continuous integration of massive volumes of new user interaction data into training pipelines. While GPUs have scale…

cs.AR2024★ 1 cited

Efficient Tabular Data Preprocessing of ML Pipelines

Yu Zhu, Wenqi Jiang, Gustavo Alonso

Data preprocessing pipelines, which includes data decoding, cleaning, and transforming, are a crucial component of Machine Learning (ML) training. Thy are computationally intensive…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.