Sequence segmentation is a flexible and highly accurate mechanism for modeling several applications. Inference on segmentation models involves dynamic programming computations tha...
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
Abstract. We introduce an ontology-based semantic modelling framework that addresses subject domain modelling, instruction modelling, and interoperability aspects in the developmen...