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ANSS
2006
IEEE
15 years 11 months ago
A New Approach for Computing Conditional Probabilities of General Stochastic Processes
In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develo...
Fabian Wickborn, Claudia Isensee, Thomas Simon, Sa...
CVPR
2009
IEEE
16 years 12 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
CVPR
2007
IEEE
16 years 6 months ago
Hierarchical Matching of Deformable Shapes
We describe a new hierarchical representation for twodimensional objects that captures shape information at multiple levels of resolution. This representation is based on a hierar...
Pedro F. Felzenszwalb, Joshua D. Schwartz
ICPR
2008
IEEE
16 years 6 months ago
Feature Fusion Hierarchies for gender classification
We present a hierarchical feature fusion model for image classification that is constructed by an evolutionary learning algorithm. The model has the ability to combine local patch...
Fabien Scalzo, George Bebis, Mircea Nicolescu, Lea...
RECOMB
2006
Springer
16 years 5 months ago
Maximal Accurate Forests from Distance Matrices
Abstract. We present a fast converging method for distance-based phylogenetic inference, which is novel in two respects. First, it is the only method (to our knowledge) to guarante...
Constantinos Daskalakis, Cameron Hill, Alexander J...