most citedRe-thinking Federated Active Learning based on Inter-class Diversity

3 citations · 3 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2023

Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning

Sungnyun Kim, Sangmin Bae, Se-Young Yun

Deep learning in general domains has constantly been extended to domain-specific tasks requiring the recognition of fine-grained characteristics. However, real-world applications f…

cs.CV2023★ 3 cited

Re-thinking Federated Active Learning based on Inter-class Diversity

SangMook Kim, Sangmin Bae, Hwanjun Song +1

Although federated learning has made awe-inspiring advances, most studies have assumed that the client's data are fully labeled. However, in a real-world scenario, every client may…