Abstract. This work presents methods for processing a constraint satisfaction problem (CSP) formulated by an expression-based language, before the CSP is presented to a stochastic ...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system...
Compressed Sensing is a new paradigm for acquiring the compressible signals that arise in many applications. These signals can be approximated using an amount of information much ...
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp,...
The SENSORIA Reference Modelling Language (SRML) provides primitives for modelling business processes in a technology agnostic way. At the core of SRML is the notion of module as a...