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» The intrinsic dimensionality of graphs
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APPROX
2010
Springer
176views Algorithms» more  APPROX 2010»
13 years 11 months ago
Approximation Algorithms for Min-Max Generalization Problems
Abstract. We provide improved approximation algorithms for the minmax generalization problems considered by Du, Eppstein, Goodrich, and Lueker [1]. In min-max generalization proble...
Piotr Berman, Sofya Raskhodnikova
AVSS
2009
IEEE
13 years 7 months ago
Landmark Localisation in 3D Face Data
A comparison of several approaches that use graph matching and cascade filtering for landmark localisation in 3D face data is presented. For the first method, we apply the structur...
Marcelo Romero, Nick Pears
PRL
2010
188views more  PRL 2010»
13 years 8 months ago
Sparsity preserving discriminant analysis for single training image face recognition
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Lishan Qiao, Songcan Chen, Xiaoyang Tan
CVPR
2008
IEEE
15 years 8 hour ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 11 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...