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NIPS
1998
13 years 8 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
ICA
2010
Springer
13 years 7 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
SDM
2010
SIAM
166views Data Mining» more  SDM 2010»
13 years 5 months ago
Directed Network Community Detection: A Popularity and Productivity Link Model
In this paper, we consider the problem of community detection in directed networks by using probabilistic models. Most existing probabilistic models for community detection are ei...
Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, ...
PAMI
1998
107views more  PAMI 1998»
13 years 6 months ago
Graph Matching With a Dual-Step EM Algorithm
—This paper describes a new approach to matching geometric structure in 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifyi...
Andrew D. J. Cross, Edwin R. Hancock
FTTCS
2006
132views more  FTTCS 2006»
13 years 6 months ago
Algorithms and Data Structures for External Memory
Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast ...
Jeffrey Scott Vitter