Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict ...
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statis...