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NIPS
2008
13 years 9 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
ICDM
2006
IEEE
122views Data Mining» more  ICDM 2006»
14 years 1 months ago
Optimal Segmentation Using Tree Models
Sequence data are abundant in application areas such as computational biology, environmental sciences, and telecommunications. Many real-life sequences have a strong segmental str...
Robert Gwadera, Aristides Gionis, Heikki Mannila
CVPR
2005
IEEE
14 years 9 months ago
Bayesian 3D Modeling from Images Using Multiple Depth Maps
This paper addresses the problem of reconstructing the geometry and color of a Lambertian scene, given some fully calibrated images acquired with wide baselines. In order to compl...
Pau Gargallo, Peter F. Sturm
PAMI
2008
189views more  PAMI 2008»
13 years 7 months ago
Detecting Objects of Variable Shape Structure With Hidden State Shape Models
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
CSDA
2008
91views more  CSDA 2008»
13 years 7 months ago
Model-based clustering for longitudinal data
A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
Rolando De la Cruz-Mesía, Fernando A. Quint...