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A Survey on Multi-view Learning
TLDR
We review a number of representative multi-view learning algorithms in different areas and classify them into three groups: 1) co-training, 2) multiple kernel learning, and 3) subspace learning. Expand
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Multi-View Intact Space Learning
  • Chang Xu, D. Tao, Chao Xu
  • Mathematics, Computer Science
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 December 2015
TLDR
We propose the Multi-view Intact Space Learning (MISL) algorithm, which integrates the encoded complementary information in multiple views to discover a latent intact representation of the data, and show that the complementarity between multiple views is beneficial for the stability and generalization. Expand
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Status of metal accumulation in farmland soils across China: from distribution to risk assessment.
Increasing metal pollution has drawn broad public attention in China due to severe environmental quality deterioration. However, so far, there has been no study to survey metal accumulation inExpand
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Status of phthalate esters contamination in agricultural soils across China and associated health risks.
The extensive utilization of phthalate-containing products has lead to ubiquitous contamination of phthalate esters (PAEs) in various matrices. However, comprehensive knowledge of their pollution inExpand
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Ensemble Manifold Regularization
TLDR
We propose an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Expand
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Robust Extreme Multi-label Learning
TLDR
This paper explores and exploits an additional sparse component to handle tail labels behaving as outliers, in order to make the classical low-rank principle in multi-label learning valid. Expand
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Evaluating the comparative efficiency of Chinese third‐party logistics providers using data envelopment analysis
Purpose – The purpose of this paper is to develop a benchmark of performance standards for Chinese third‐party logistics providers (3PLs) in the emerging market. It also intends to identify variousExpand
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Data-Free Learning of Student Networks
  • H. Chen, Yunhe Wang, +6 authors Qi Tian
  • Computer Science, Mathematics
  • IEEE/CVF International Conference on Computer…
  • 2 April 2019
TLDR
Learning portable neural networks is very essential for computer vision for the purpose that pre-trained heavy deep models can be well applied on edge devices such as mobile phones and micro sensors. Expand
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Self-calibrating photometric stereo
We present a self-calibrating photometric stereo method. From a set of images taken from a fixed viewpoint under different and unknown lighting conditions, our method automatically determines aExpand
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Tensor Canonical Correlation Analysis for Multi-View Dimension Reduction
TLDR
In this work, we develop tensor CCA (TCCA) which straightforwardly yet naturally generalizes CCA to handle the data of an arbitrary number of views by analyzing the covariance tensor of the different views. Expand
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