most citedDistributed Parameter Estimation via Pseudo-likelihood

26 citations · 126 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI20122 cited

A Cluster-Cumulant Expansion at the Fixed Points of Belief Propagation

Max Welling, Andrew E. Gelfand, Alexander T. Ihler

We introduce a new cluster-cumulant expansion (CCE) based on the fixed points of iterative belief propagation (IBP). This expansion is similar in spirit to the loop-series (LS) rec…

cs.AI201223 cited

Belief Propagation for Structured Decision Making

Qiang Liu, Alexander T. Ihler

Variational inference algorithms such as belief propagation have had tremendous impact on our ability to learn and use graphical models, and give many insights for developing or un…

cs.AI201219 cited

Join-graph based cost-shifting schemes

Alexander T. Ihler, Natalia Flerova, Rina Dechter +1

We develop several algorithms taking advantage of two common approaches for bounding MPE queries in graphical models: minibucket elimination and message-passing updates for linear…

cs.CV20128 cited

Fast Planar Correlation Clustering for Image Segmentation

Julian Yarkony, Alexander T. Ihler, Charless C. Fowlkes

We describe a new optimization scheme for finding high-quality correlation clusterings in planar graphs that uses weighted perfect matching as a subroutine. Our method provides low…

stat.ME20126 cited

Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation

Ian Porteous, Alexander T. Ihler, Padhraic Smyth +1

Nonparametric Bayesian approaches to clustering, information retrieval, language modeling and object recognition have recently shown great promise as a new paradigm for unsupervise…

cs.LG201226 cited

Distributed Parameter Estimation via Pseudo-likelihood

Qiang Liu, Alexander Ihler

Estimating statistical models within sensor networks requires distributed algorithms, in which both data and computation are distributed across the nodes of the network. We propose…