We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
We present a parameter inference algorithm for autonomous stochastic linear hybrid systems, which computes a maximum-likelihood model, given only a set of continuous output data of...
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
Abstract. We study the type system introduced by Boyapati and Rinard in their paper “A Parameterized Type System for Race-Free Java Programs” and try to infer the type annotati...
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...