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» Some Results on Greedy Embeddings in Metric Spaces
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CVPR
2008
IEEE
15 years 11 months ago
Human action recognition using Local Spatio-Temporal Discriminant Embedding
Human action video sequences can be considered as nonlinear dynamic shape manifolds in the space of image frames. In this paper, we address learning and classifying human actions ...
Kui Jia, Dit-Yan Yeung
AAAI
2010
14 years 6 months ago
Multilinear Maximum Distance Embedding Via L1-Norm Optimization
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Yang Liu, Yan Liu, Keith C. C. Chan
FOCS
2006
IEEE
15 years 3 months ago
Algorithms on negatively curved spaces
d abstract] Robert Krauthgamer ∗ IBM Almaden James R. Lee † Institute for Advanced Study We initiate the study of approximate algorithms on negatively curved spaces. These spa...
Robert Krauthgamer, James R. Lee
LCTRTS
2007
Springer
15 years 3 months ago
Combining source-to-source transformations and processor instruction set extensions for the automated design-space exploration o
Industry’s demand for flexible embedded solutions providing high performance and short time-to-market has led to the development of configurable and extensible processors. The...
Richard Vincent Bennett, Alastair Colin Murray, Bj...
PAMI
2006
141views more  PAMI 2006»
14 years 9 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee