Computational Learning Theory
Improved Algorithms for Collaborative PAC Learning
Neural Information Processing Systems http://nips.cc/
Learning convex polytopes with margin
Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch
Fortheformer setting, an extensive literature has explored the statistical and computational aspects of learning Booleanfunctions[Angluin,1992,HellersteinandServedio,2007].
Credal Learning Theory
Statistical learning theory is the foundation of machine learning, providing theoretical bounds for the risk of models learned from a (single) training set, assumed to issue from an unknown probability distribution.
On Robustness to Adversarial Examples and Polynomial Optimization
Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
Neural Information Processing Systems http://nips.cc/