Hanneke
PulseAugur coverage of Hanneke — every cluster mentioning Hanneke across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
New Algorithm Boosts Adversarial Robustness in Learning Models
Researchers have developed a new algorithm that significantly improves the ability to learn predictors robust to adversarial examples. This method achieves linear sample complexity in the VC dimension, an exponential im…
-
New research decouples single-instance learning rates from direct-sum rates
A new research paper by Hanneke, Moran, and Waknine explores the relationship between agnostic PAC learning curves and direct sums in machine learning. The study demonstrates that the learning rate of a single instance …
-
New VC dimension bounds for partial concept classes in L_p spaces
Researchers have extended the concept of VC dimension to partial functions, specifically focusing on geometric partial concept classes (PCCs) in real Banach spaces. They established dimension-free upper bounds for the V…
-
New research proves optimal sample complexity for multiclass learning
Researchers have resolved a long-standing question regarding the optimal sample complexity for multiclass classification problems. Their work establishes a connection between the DS dimension and hypergraph density, pro…