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JMLR
2010
129views more  JMLR 2010»
14 years 11 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
SIGIR
2010
ACM
15 years 8 months ago
Probabilistic latent maximal marginal relevance
Diversity has been heavily motivated in the information retrieval literature as an objective criterion for result sets in search and recommender systems. Perhaps one of the most w...
Shengbo Guo, Scott Sanner
ACL
2004
15 years 5 months ago
Chinese Verb Sense Discrimination Using an EM Clustering Model with Rich Linguistic Features
This paper discusses the application of the Expectation-Maximization (EM) clustering algorithm to the task of Chinese verb sense discrimination. The model utilized rich linguistic...
Jinying Chen, Martha Stone Palmer
ICCV
2007
IEEE
16 years 6 months ago
Scene Modeling Using Co-Clustering
In this paper, we propose a novel approach for scene modeling. The proposed method is able to automatically discover the intermediate semantic concepts. We utilize Maximization of...
Jingen Liu, Mubarak Shah
142
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IJCAI
2007
15 years 5 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...