Abstract-- Policy Gradients with Parameter-based Exploration (PGPE) is a novel model-free reinforcement learning method that alleviates the problem of high-variance gradient estima...
Frank Sehnke, Alex Graves, Christian Osendorfer, J...
Convergence is often the key liveness property for distributed systems that interact with physical processes. Techniques for proving convergence (asymptotic stability) have been ex...
While most popular collaborative filtering methods use low-rank matrix factorization and parametric density assumptions, this article proposes an approach based on distribution-fr...
—Default ARTMAP combines winner-take-all category node activation during training, distributed activation during testing, and a set of default parameter values that define a read...
Ontologies provide a means of modelling and representing a knowledge domain. Such representation, already used in purpose-built distributed information systems, can also be of gre...
Nickolas J. G. Falkner, Paul D. Coddington, Andrew...