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158
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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
TNN
2008
129views more  TNN 2008»
15 years 4 months ago
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
Johan A. K. Suykens
AAAI
2006
15 years 6 months ago
Extending Dynamic Backtracking to Solve Weighted Conditional CSPs
Many planning and design problems can be characterized as optimal search over a constrained network of conditional choices with preferences. To draw upon the advanced methods of c...
Robert T. Effinger, Brian C. Williams
JMLR
2008
79views more  JMLR 2008»
15 years 4 months ago
Manifold Learning: The Price of Normalization
We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consis...
Yair Goldberg, Alon Zakai, Dan Kushnir, Yaacov Rit...
159
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PAMI
2011
14 years 7 months ago
Silhouette Segmentation in Multiple Views
— In this paper, we present a method for extracting consistent foreground regions when multiple views of a scene are available. We propose a framework that automatically identiï¬...
Wonwoo Lee, Woontack Woo, Edmond Boyer