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cs.LG2025
Diffusion Disambiguation Models for Partial Label Learning
Jinfu Fan, Xiaohui Zhong, Kangrui Ren +4
Learning from ambiguous labels is a long-standing problem in practical machine learning applications. The purpose of \emph{partial label learning} (PLL) is to identify the ground-t…
cs.LG2025
FedRS-Bench: Realistic Federated Learning Datasets and Benchmarks in Remote Sensing
Haodong Zhao, Peng Peng, Chiyu Chen +2
Remote sensing (RS) images are usually produced at an unprecedented scale, yet they are geographically and institutionally distributed, making centralized model training challengin…