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» Topologically-constrained latent variable models
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ECCV
2006
Springer
14 years 11 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
IDA
2009
Springer
13 years 7 months ago
Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
Florian Blöchl, Fabian J. Theis
PERVASIVE
2009
Springer
14 years 4 months ago
Methodologies for Continuous Cellular Tower Data Analysis
This paper presents novel methodologies for the analysis of continuous cellular tower data from 215 randomly sampled subjects in a major urban city. We demonstrate the potential of...
Nathan Eagle, John A. Quinn, Aaron Clauset
NIPS
2008
13 years 11 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
ICCV
2005
IEEE
14 years 11 months ago
Beyond Trees: Common-Factor Models for 2D Human Pose Recovery
Tree structured models have been widely used for determining the pose of a human body, from either 2D or 3D data. While such models can effectively represent the kinematic constra...
Xiangyang Lan, Daniel P. Huttenlocher