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ICCV
2011
IEEE
13 years 9 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
14 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
CLUSTER
2005
IEEE
15 years 3 months ago
Fast Query Processing by Distributing an Index over CPU Caches
Data intensive applications on clusters often require requests quickly be sent to the node managing the desired data. In many applications, one must look through a sorted tree str...
Xiaoqin Ma, Gene Cooperman
CSB
2003
IEEE
15 years 2 months ago
LOGOS: a modular Bayesian model for de novo motif detection
The complexity of the global organization and internal structures of motifs in higher eukaryotic organisms raises significant challenges for motif detection techniques. To achiev...
Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M...
CORR
2010
Springer
172views Education» more  CORR 2010»
14 years 9 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang