166 citations · 1.4k across the 47 of their papers we have counts for
5 papers · 2 filters
Learning Mixtures of Submodular Shells with Application to Document Summarization
Hui Lin, Jeff A. Bilmes
We introduce a method to learn a mixture of submodular "shells" in a large-margin setting. A submodular shell is an abstract submodular function that can be instantiated with a gro…
PAC-learning bounded tree-width Graphical Models
Mukund Narasimhan, Jeff A. Bilmes
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Previ…
A submodular-supermodular procedure with applications to discriminative structure learning
Mukund Narasimhan, Jeff A. Bilmes
In this paper, we present an algorithm for minimizing the difference between two submodular functions using a variational framework which is based on (an extension of) the concave-…
Consensus ranking under the exponential model
Marina Meila, Kapil Phadnis, Arthur Patterson +1
We analyze the generalized Mallows model, a popular exponential model over rankings. Estimating the central (or consensus) ranking from data is NP-hard. We obtain the following new…
Active Semi-Supervised Learning using Submodular Functions
Andrew Guillory, Jeff A. Bilmes
We consider active, semi-supervised learning in an offline transductive setting. We show that a previously proposed error bound for active learning on undirected weighted graphs ca…