125 citations · 1.2k across the 71 of their papers we have counts for
4 papers · 1 filter
MAD-Bayes: MAP-based Asymptotic Derivations from Bayes
Tamara Broderick, Brian Kulis, Michael I. Jordan
The classical mixture of Gaussians model is related to K-means via small-variance asymptotics: as the covariances of the Gaussians tend to zero, the negative log-likelihood of the…
Real-time semiparametric regression
Jan Luts, Tamara Broderick, Matt P. Wand
We develop algorithms for performing semiparametric regression analysis in real time, with data processed as it is collected and made immediately available via modern telecommunica…
Cluster and Feature Modeling from Combinatorial Stochastic Processes
Tamara Broderick, Michael I. Jordan, Jim Pitman
One of the focal points of the modern literature on Bayesian nonparametrics has been the problem of clustering, or partitioning, where each data point is modeled as being associate…
Combining Spatial and Telemetric Features for Learning Animal Movement Models
Berk Kapicioglu, Robert E. Schapire, Martin Wikelski +1
We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with…