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Ming-Zhao Yang

5 papers hereh-index 4135 citations8 works total

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

author position
  • first author3
  • middle author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20222024
most citedCross-domain Federated Object Detection

17 citations · 24 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models

Mingzhao Yang, Shangchao Su, Bin Li +1

In recent years, the attention towards One-Shot Federated Learning (OSFL) has been driven by its capacity to minimize communication. With the development of the diffusion model (DM…

cs.CV2023★ 1 cited

One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models

Mingzhao Yang, Shangchao Su, Bin Li +1

In recent years, One-shot Federated Learning methods based on Diffusion Models have garnered increasing attention due to their remarkable performance. However, most of these method…

cs.CV2023★ 2 cited

Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model

Mingzhao Yang, Shangchao Su, Bin Li +1

Recently, semi-supervised federated learning (semi-FL) has been proposed to handle the commonly seen real-world scenarios with labeled data on the server and unlabeled data on the…

cs.CV2022★ 17 cited

Cross-domain Federated Object Detection

Shangchao Su, Bin Li, Chengzhi Zhang +2

Detection models trained by one party (including server) may face severe performance degradation when distributed to other users (clients). Federated learning can enable multi-part…

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