190 citations · 633 across the 32 of their papers we have counts for
5 papers · 1 filter
Variational Optimization
Joe Staines, David Barber
We discuss a general technique that can be used to form a differentiable bound on the optima of non-differentiable or discrete objective functions. We form a unified description of…
Bayesian Conditional Cointegration
Chris Bracegirdle, David Barber
Cointegration is an important topic for time-series, and describes a relationship between two series in which a linear combination is stationary. Classically, the test for cointegr…
Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices
David Barber
We introduce Clique Matrices as an alternative representation of undirected graphs, being a generalisation of the incidence matrix representation. Here we use clique matrices to de…
An Approximate Newton Method for Markov Decision Processes
Thomas Furmston, David Barber
Gradient-based algorithms are one of the methods of choice for the optimisation of Markov Decision Processes. In this article we will present a novel approximate Newton algorithm f…
Efficient Inference in Markov Control Problems
Thomas Furmston, David Barber
Markov control algorithms that perform smooth, non-greedy updates of the policy have been shown to be very general and versatile, with policy gradient and Expectation Maximisation…