Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuse...
Yanlei Diao, Boduo Li, Anna Liu, Liping Peng, Char...
Desktop search is an important part of personal information management (PIM). However, research in this area has been limited by the lack of shareable test collections, making cum...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...