2 papers
stat.ML2025
PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita +3
One of the most basic lower bounds in machine learning is that in nearly any nontrivial setting, it takes samples to learn to error (and more, if the…
cs.LG2025
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees
Ally Yalei Du, Eric Huang, Dravyansh Sharma
Graph-based semi-supervised learning is a powerful paradigm in machine learning for modeling and exploiting the underlying graph structure that captures the relationship between la…