Abstract. Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properti...
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
Computer games accessibility have initially been regarded as an area of minor importance as there were much more "serious" topics to focus on. Today, the society is slowl...
Dominique Archambault, Thomas Gaudy, Klaus Miesenb...
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
We introduce the Spherical Admixture Model (SAM), a Bayesian topic model for arbitrary 2 normalized data. SAM maintains the same hierarchical structure as Latent Dirichlet Allocat...
Joseph Reisinger, Austin Waters, Bryan Silverthorn...