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SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
13 years 9 months ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
ECCV
2004
Springer
14 years 9 months ago
Many-to-Many Feature Matching Using Spherical Coding of Directed Graphs
In recent work, we presented a framework for many-to-many matching of multi-scale feature hierarchies, in which features and their relations were captured in a vertex-labeled, edge...
M. Fatih Demirci, Ali Shokoufandeh, Sven J. Dickin...
ICPR
2000
IEEE
14 years 7 days ago
Comparison between Two Prototype Representation Schemes for a Nearest Neighbor Classifier
2. Character Recognition System The paper is about the problem of finding good prototypes for a condensed nearest neighbor classifiei- in a recognition system. A comparison study ...
Jari Kangas
ICPR
2006
IEEE
14 years 9 months ago
Dissimilarity-based classification for vectorial representations
General dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. They arise in problems in which direct comparisons of objects are made, e....
Elzbieta Pekalska, Robert P. W. Duin
ICRA
2010
IEEE
134views Robotics» more  ICRA 2010»
13 years 6 months ago
Understanding and executing instructions for everyday manipulation tasks from the World Wide Web
Service robots will have to accomplish more and more complex, open-ended tasks and regularly acquire new skills. In this work, we propose a new approach to generating plans for su...
Moritz Tenorth, Daniel Nyga, Michael Beetz