In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
Wireless sensor networks are often required to provide event miss-ratio assurance for a given event type. To meet such assurances along with minimum energy consumption, this paper ...
—Some data mining problems require predictive models to be not only accurate but also comprehensible. Comprehensibility enables human inspection and understanding of the model, m...
Many software security solutions require accurate tracking of control/data dependencies among information objects in network applications. This paper presents a general dynamic in...
The last decade witnessed the extensive studies of algorithms for data streams. In this model, the input is given as a sequence of items passing only once or a few times, and we ar...