PQ and TDS learning are equivalent in the distribution-free setting for Boolean classes, implying hardness for TDS halfspace learning but efficient algorithms with membership queries.
Advances in neural information processing systems , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
DPS quantifies deviation of per-sample decision patterns from class averages and shows linear correlation with generalization gaps while unifying degradation scenarios into a continuous trajectory.
citing papers explorer
-
Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift
PQ and TDS learning are equivalent in the distribution-free setting for Boolean classes, implying hardness for TDS halfspace learning but efficient algorithms with membership queries.
-
Understanding Generalization through Decision Pattern Shift
DPS quantifies deviation of per-sample decision patterns from class averages and shows linear correlation with generalization gaps while unifying degradation scenarios into a continuous trajectory.