A large number of problems in computer vision can be modeled as energy minimization problems in a markov random field (MRF) framework. Many methods have been developed over the y...
Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
We generalize the primal-dual hybrid gradient (PDHG) algorithm proposed by Zhu and Chan in [M. Zhu, and T. F. Chan, An Efficient Primal-Dual Hybrid Gradient Algorithm for Total Var...
A prospective study of the use of ordered multi-lattices as underlying sets of truth-values for a generalised framework of logic programming is presented. Specifically, we investi...
The problem of locating centers for radial basis functions in neural networks is discussed. The proposed approach allows us to apply the results from the theory of optimum experime...