In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
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...
We prove new lower bounds for learning intersections of halfspaces, one of the most important concept classes in computational learning theory. Our main result is that any statist...