We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
This paper studies face recognition and person-specific face image retrieval in unconstrained environments. The proposed method consists of two parts: offline and online learning....
Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...