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» Reductions among high dimensional proximity problems
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ICDE
2007
IEEE
211views Database» more  ICDE 2007»
15 years 12 months ago
Document Representation and Dimension Reduction for Text Clustering
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...
NIPS
1997
15 years 6 months ago
Mapping a Manifold of Perceptual Observations
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Joshua B. Tenenbaum
PAMI
2012
13 years 8 months ago
Aggregating Local Image Descriptors into Compact Codes
— This paper addresses the problem of large-scale image search. Three constraints have to be taken into account: search accuracy, efficiency, and memory usage. We first present...
Hervé Jégou, Florent Perronnin, Matt...
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GLOBECOM
2007
IEEE
15 years 12 months ago
Joint Reduction of Peak-to-Average Power Ratio and Out-of-Band Power in OFDM Systems
—The high peak-to-average power ratio is a major drawback of OFDM systems. Many PAPR reduction techniques have been proposed in the literature, among them a method that uses a su...
Martin Senst, Markus Jordan, Meik Dorpinghaus, Mic...
IJCAI
2007
15 years 7 months ago
A Subspace Kernel for Nonlinear Feature Extraction
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Mingrui Wu, Jason D. R. Farquhar