— Assisting humans in their daily lives requires robots to be proficient in manual tasks and effective in communicating states/intentions with human users. This paper advocates ...
In this article we present an infrastructure for creating mash up visual representations of the user profile that combines data from different sources. We explored this approach ...
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
This work proposes a learning method for deep architectures that takes advantage of sequential data, in particular from the temporal coherence that naturally exists in unlabeled v...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...