3 papers
cs.LG2026
Can Domain Generalization be Guaranteed in Small-Sample Learning?
Hong Zheng
The small-sample learning problem remains a fundamental challenge in machine learning because limited training data lead to unstable model estimation and generalization. Structural…
cs.LG2026
How Many Samples Are Enough for Learning Across Domains?
Hong Zheng
Understanding the fundamental mechanisms of learning is essential for designing systems with strong generalization. Recent studies have shown that increasing the number of training…
cs.LG2026
Distribution Shift Is Key to Learning Invariant Prediction
Hong Zheng, Fei Teng
An interesting phenomenon arises: Empirical Risk Minimization (ERM) sometimes outperforms methods specifically designed for out-of-distribution tasks. This motivates an investigati…