The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
Abstract. Here we study the plausibility of a phase oscillators dynamical model for time division for multiple access in wireless communication networks. We show that emerging patt...
Abstract. Debugging virtual machines (VMs) presents unique challenges, especially meta-circular VMs, which are written in the same language they implement. Making sense of runtime ...
Interest has been growing within HCI on the use of machine learning and reasoning in applications to classify such hidden states as user intentions, based on observations. HCI res...
Ashish Kapoor, Bongshin Lee, Desney S. Tan, Eric H...
This paper demonstrates that the waves produced on the surface of water can be used as the medium for a “Liquid State Machine” that pre-processes inputs so allowing a simple pe...