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SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
14 years 11 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
15 years 11 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
15 years 2 months 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
15 years 11 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»
14 years 8 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