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In this paper, we consider de-noising as well as dimensionality reduction by proposing a novel method named Robust Integrated Locally Linear Embedding. The�...
tion named Robust Integrated Locally Linear Embedding(RILLE), which gains embedding of data by learning a robust similarity function that is low-rank, semi-.
In this paper, we address the outlier problem in the context of LLE. Based on robust PCA techniques, we propose an approach to make LLE more robust.
Oct 15, 2017In this paper, we present a new model for learning robust locally-linear controllable embedding (RCE). Our model directly estimates the predictive conditional�...
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Dec 4, 2012The method combines the two steps in LLE into a single framework and deals with de-noising by solving a l2,1-l2 mixed norm based optimization�...
This paper proposes a robust locally nonlinear embedding (RLNE) method to alleviate the impact of noise.
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In this paper, we consider de-noising as well as dimensionality reduction by proposing a novel method named Robust Integrated Locally Linear Embedding. The�...
Locally Linear Embedding (LLE) is a powerful technique for nonlinear dimensionality reduction and manifold learning, enabling the simplification of complex�...
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In this paper, we address this problem in the context of the Hessian locally linear embedding (HLLE) algorithm and propose a more robust method, called RHLLE.
The locally linear embedding (LLE) algorithm has recently emerged as a promising technique for dimensional reduction and feature extraction because it preserves�...
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