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» A Hierarchical Latent Variable Model for Data Visualization
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JMLR
2010
192views more  JMLR 2010»
13 years 4 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
CVPR
2007
IEEE
14 years 12 months ago
Tracking Large Variable Numbers of Objects in Clutter
We propose statistical data association techniques for visual tracking of enormously large numbers of objects. We do not assume any prior knowledge about the numbers involved, and...
Margrit Betke, Diane E. Hirsh, Angshuman Bagchi, N...
CVPR
2011
IEEE
13 years 6 months ago
Recognizing Human Actions by Attributes
In this paper we explore the idea of using high-level semantic concepts, also called attributes, to represent human actions from videos and argue that attributes enable the constr...
Jingen Liu
ACSC
2004
IEEE
14 years 1 months ago
Flexible Layering in Hierarchical Drawings with Nodes of Arbitrary Size
Graph drawing is an important area of information visualization which concerns itself with the visualization of relational data structures. Relational data like networks, hierarch...
Carsten Friedrich, Falk Schreiber
PAMI
2010
205views more  PAMI 2010»
13 years 8 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille