2 papers
cs.DC2026
SatDL: Jointly Optimizing Data Redistribution and Training for Satellite-Based Distributed Learning
Hao Wu, Kin Whye Chew, Yizhan Han +2
Satellite-based distributed learning promises to train machine-learning models directly in orbit using massive, globally dispersed sensor data, thereby avoiding large-scale data do…
cs.LG2026
Cumulative Meta-Learning from Active Learning Queries for Robustness to Spurious Correlations
Kin Whye Chew, Jingxian Wang
Spurious correlations in real-world datasets cause machine learning models to rely on irrelevant patterns, undermining reliability, generalization, and fairness. Active learning of…