Abstract. The automata-based model checking approach for randomized distributed systems relies on an operational interleaving semantics of the system by means of a Markov decision ...
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
The goal of this paper is to explore the effects of synchronization on distributed decision making processes. In particular, we examine the dynamics of a spatially distributed mul...
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...