This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
—Most existing wireless ad hoc routing protocols rely upon the use of backward learning technique with explicit control messages to route packets. In this paper we propose a set ...
Companies such as Zara and World Co. have recently implemented novel product development processes and supply chain architectures enabling them to make more product design and ass...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...