In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Image parsing remains difficult due to the need to combine
local and contextual information when labeling a
scene. We approach this problem by using the epitome as a
prior over ...
Jonathan Warrell, Simon J. D. Prince, Alastair P. ...
We show how to use a sampling method to find sparsely clad people in static images. People are modeled as an assembly of nine cylindrical segments. Segments are found using an EM ...
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...