This tutorial provides a comprehensive and comparative overview of general techniques to efficiently support similarity queries in spatial, temporal, spatio-temporal, and multimedi...
In this paper, we present a new approach for continuous probabilistic mapping. The objective is to build metric maps of unknown environments through cooperation between multiple au...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Abstract. In this paper we show how Metropolis Light Transport can be extended both in the underlying theoretical framework and the algorithmic implementation to incorporate volume...
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...