Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
We propose a lattice-based functional encryption scheme for inner product predicates whose security follows from the difficulty of the learning with errors (LWE) problem. This co...
Shweta Agrawal, David Mandell Freeman, Vinod Vaiku...
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
Efficient learning of DFA is a challenging research problem in grammatical inference. It is known that both exact and approximate (in the PAC sense) identifiability of DFA is har...