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138
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COLT
2004
Springer
16 years 13 days ago
Inferring Mixtures of Markov Chains
We define the problem of inferring a “mixture of Markov chains” based on observing a stream of interleaved outputs from these chains. We show a sharp characterization of the i...
Tugkan Batu, Sudipto Guha, Sampath Kannan
CVPR
2009
IEEE
17 years 2 months ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...
156
Voted
CORR
2006
Springer
90views Education» more  CORR 2006»
15 years 7 months ago
On entropy for mixtures of discrete and continuous variables
Let X be a discrete random variable with support S and f : S S be a bijection. Then it is wellknown that the entropy of X is the same as the entropy of f(X). This entropy preserva...
Chandra Nair, Balaji Prabhakar, Devavrat Shah
ICCV
2007
IEEE
16 years 9 months ago
Non-Parametric Probabilistic Image Segmentation
We propose a simple probabilistic generative model for image segmentation. Like other probabilistic algorithms (such as EM on a Mixture of Gaussians) the proposed model is princip...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
187
Voted
ISBI
2008
IEEE
16 years 7 months ago
Robust maximum likelihood estimation in Q-space MRI
Q-space imaging is an emerging diffusion weighted MR imaging technique to estimate molecular diffusion probability density functions (PDF's) without the need to assume a Gaus...
Bennett A. Landman, Jonathan A. D. Farrell, Seth A...