Today's networks are becoming increasingly complex and the ability to effectively and efficiently operate and manage them is ever more challenging. Ways to provide end-to-end...
Quantum systems are promising candidates of future computing and information processing devices. In a large system, information about the quantum states and processes may be incomp...
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifier...
Antonio Torralba, Kevin P. Murphy, William T. Free...
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...