—The particle swarm optimizer (PSO) is a popular computing technique of swarm intelligence, known for its fast convergence speed and easy implementation. All the particles in the...
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
The main difficulty in the formalization of a static analysis framework for CC programs is probably related to the correct approximation of the entailment relation between constrai...
An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...