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» Semi-supervised nonlinear dimensionality reduction
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CVPR
2008
IEEE
14 years 10 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic
NIPS
2003
13 years 10 months ago
Non-linear CCA and PCA by Alignment of Local Models
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
NIPS
2008
13 years 10 months ago
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Yuhong Guo
ICASSP
2008
IEEE
14 years 3 months ago
A study of using locality preserving projections for feature extraction in speech recognition
This paper presents a new approach to feature analysis in automatic speech recognition (ASR) based on locality preserving projections (LPP). LPP is a manifold based dimensionality...
Yun Tang, Richard Rose
ICPR
2010
IEEE
13 years 11 months ago
Temporal Extension of Laplacian Eigenmaps for Unsupervised Dimensionality Reduction of Time Series
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
Michal Lewandowski, Jesus Martinez-Del-Rincon, Dim...