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COLT
2004
Springer
15 years 12 months 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 1 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),...
CORR
2006
Springer
90views Education» more  CORR 2006»
15 years 6 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 8 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
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...