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» Information Preserving Dimensionality Reduction
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116
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CVPR
2010
IEEE
15 years 11 months ago
Manifold Blurring Mean Shift Algorithms
We propose a new family of algorithms for denoising data assumed to lie on a low-dimensional manifold. The algorithms are based on the blurring mean-shift update, which moves each...
Weiran Wang, Miguel Carreira-perpinan
131
Voted
ICDM
2005
IEEE
165views Data Mining» more  ICDM 2005»
15 years 9 months ago
A Bernoulli Relational Model for Nonlinear Embedding
The notion of relations is extremely important in mathematics. In this paper, we use relations to describe the embedding problem and propose a novel stochastic relational model fo...
Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. L...
144
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PKDD
2005
Springer
131views Data Mining» more  PKDD 2005»
15 years 9 months ago
ISOLLE: Locally Linear Embedding with Geodesic Distance
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
Claudio Varini, Andreas Degenhard, Tim W. Nattkemp...
149
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Evaluation of random-projection-based feature combination on speech recognition
Random projection has been suggested as a means of dimensionality reduction, where the original data are projected onto a subspace using a random matrix. It represents a computati...
Tetsuya Takiguchi, Jeff Bilmes, Mariko Yoshii, Yas...
135
Voted
SBBD
2004
94views Database» more  SBBD 2004»
15 years 4 months ago
Visual Analysis of Feature Selection for Data Mining Processes
The amount of data collected in the last decades has become a source of valuable information, allowing organizations to improve their competitiveness. However, the associated data...
Humberto Luiz Razente, Fabio Jun Takada Chino, Mar...