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JMLR
2010
137views more  JMLR 2010»
14 years 7 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
102
Voted
JMMA
2010
90views more  JMMA 2010»
14 years 7 months ago
A Unified Approach to Algorithms Generating Unrestricted and Restricted Integer Compositions and Integer Partitions
An original algorithm is presented that generates both restricted integer compositions and restricted integer partitions that can be constrained simultaneously by a) upper and low...
John Douglas Opdyke
103
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
CVPR
2012
IEEE
13 years 3 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke
CVPR
2006
IEEE
16 years 2 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...