971 citations · 3k across the 74 of their papers we have counts for
5 papers · 1 filter
Poisson intensity estimation with reproducing kernels
Seth Flaxman, Yee Whye Teh, Dino Sejdinovic
Despite the fundamental nature of the inhomogeneous Poisson process in the theory and application of stochastic processes, and its attractive generalizations (e.g. Cox process), fe…
CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT
Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek +5
In forthcoming years, the Internet of Things (IoT) will connect billions of smart devices generating and uploading a deluge of data to the cloud. If successfully extracted, the kno…
Large-Scale Kernel Methods for Independence Testing
Qinyi Zhang, Sarah Filippi, Arthur Gretton +1
Representations of probability measures in reproducing kernel Hilbert spaces provide a flexible framework for fully nonparametric hypothesis tests of independence, which can captur…
Bayesian Learning of Kernel Embeddings
Seth Flaxman, Dino Sejdinovic, John P. Cunningham +1
Kernel methods are one of the mainstays of machine learning, but the problem of kernel learning remains challenging, with only a few heuristics and very little theory. This is of p…
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Performing exact posterior inference in complex generative models is often difficult or impossible due to an expensive to evaluate or intractable likelihood function. Approximate B…